U.S. patent number 8,476,545 [Application Number 12/826,315] was granted by the patent office on 2013-07-02 for sorting pieces of material based on photonic emissions resulting from multiple sources of stimuli.
This patent grant is currently assigned to Spectramet, LLC. The grantee listed for this patent is R. Lynn Conley, Richard E. Hill, Robert H. Parrish, Charles E. Roos, Edward J. Sommer, David B. Spencer. Invention is credited to R. Lynn Conley, Richard E. Hill, Robert H. Parrish, Charles E. Roos, Edward J. Sommer, David B. Spencer.
United States Patent |
8,476,545 |
Sommer , et al. |
July 2, 2013 |
**Please see images for:
( Certificate of Correction ) ** |
Sorting pieces of material based on photonic emissions resulting
from multiple sources of stimuli
Abstract
A piece of material that includes low-Z elements is classified
based on photonic emissions detected from the piece of material.
Both XRF spectroscopy and OES techniques, for example,
Laser-Induced Breakdown Spectroscopy (LIBS) and spark discharge
spectroscopy, may be used to classify the piece of material. A
stream of pieces of material are moved along a conveying system
into a stimulation and detection area. Each piece of material, in
turn, is stimulated with a first and second stimulus, of a same or
different type, causing the piece of material to emit emissions,
for example, photons, which may include at least one of x-ray
photons (i.e., x-rays) and optical emissions. These emissions then
are detected by one or to more detectors of a same or different
type. The piece of materials is then classified, for example, using
a combination of hardware, software and/or firmware, based on the
detected emissions, and then sorted.
Inventors: |
Sommer; Edward J. (Nashville,
TN), Spencer; David B. (Bedford, MA), Conley; R. Lynn
(Nashville, TN), Hill; Richard E. (Nashville, TN),
Parrish; Robert H. (Nashville, TN), Roos; Charles E.
(Nashville, TN) |
Applicant: |
Name |
City |
State |
Country |
Type |
Sommer; Edward J.
Spencer; David B.
Conley; R. Lynn
Hill; Richard E.
Parrish; Robert H.
Roos; Charles E. |
Nashville
Bedford
Nashville
Nashville
Nashville
Nashville |
TN
MA
TN
TN
TN
TN |
US
US
US
US
US
US |
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|
Assignee: |
Spectramet, LLC (Bedford,
MA)
|
Family
ID: |
42341874 |
Appl.
No.: |
12/826,315 |
Filed: |
June 29, 2010 |
Prior Publication Data
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Document
Identifier |
Publication Date |
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US 20100264070 A1 |
Oct 21, 2010 |
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Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
Issue Date |
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11986830 |
Nov 27, 2007 |
7763820 |
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10766298 |
Jan 27, 2004 |
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60442789 |
Jan 27, 2003 |
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60442735 |
Jan 27, 2003 |
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60464255 |
Apr 21, 2003 |
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Current U.S.
Class: |
209/579; 209/38;
209/212; 209/539 |
Current CPC
Class: |
B07C
5/346 (20130101); B07C 5/342 (20130101) |
Current International
Class: |
B07C
5/00 (20060101) |
Field of
Search: |
;209/38,44.1,558,564,579,580 ;378/44,45,47 |
References Cited
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WO |
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Primary Examiner: Matthews; Terrell
Attorney, Agent or Firm: Wolf, Greenfield & Sacks,
P.C.
Government Interests
GOVERNMENT RIGHTS
The U.S. Government has a paid-up license in this invention and the
right in limited circumstances to require the patent owner to
license others on reasonable terms as provided for by the terms of
Grant Nos. DMI-9901778, DMI-0128048 and DMI-0321298 awarded by
National Science Foundation and Grant No. 70NANBOH3044 awarded by
the U.S. Department of Commerce as a Cooperative Agreement with the
National Institute of Standards and Technology (NIST) under the
Advanced Technology Program (ATP).
Parent Case Text
RELATED APPLICATIONS
This application is a continuation of U.S. patent application Ser.
No. 11/986,830 (the '830 application), titled SORTING PIECES OF
MATERIAL BASED ON PHOTONIC EMISSIONS RESULTING FROM MULTIPLE
SOURCES OF STIMULI, filed Nov. 27, 2007. The '830 application is
incorporated by reference herein in its entirety. U.S. patent
application Ser. No. 11/986,830 in turn is a continuation of U.S.
patent application Ser. No. 10/766,298 (the '298 application),
titled SORTING PIECES OF MATERIAL BASED ON PHOTONIC EMISSIONS
RESULTING FROM MULTIPLE SOURCES OF STIMULI, filed Jan. 27, 2004.
The '298 application is incorporated by reference herein in its
entirety. U.S. patent application Ser. No. 10/766,298 in turn
claims the benefit under 35 U.S.C. .sctn.119(e) to commonly-owned
U.S. provisional patent application Ser. No. 60/442,789, titled
IMPROVED HIGH-SPEED MATERIAL SORTING SYSTEM, filed on Jan. 27,
2003, U.S. provisional patent application Ser. No. 60/442,735,
titled SYSTEMS AND METHODS FOR DETECTING ELEMENTS HAVING A LOW
ATOMIC NUMBER IN A MASS OF ONE OR MORE MATERIALS AND FOR DETECTING
IMPURITIES IN A MOLTEN MASS OF ONE OR MORE MATERIALS, filed on Jan.
27, 2003, and U.S. provisional patent application Ser. No.
60/464,255, titled VARIOUS SYSTEMS AND METHODS FOR HIGH SPEED
IDENTIFICATION, CLASSIFICATION, COMPOSITIONAL ANALYSIS AND SORTING
OF MATTER AND FOR DETECTING ELEMENTS HAVING A LOW ATOMIC NUMBER,
filed on Apr. 21, 2003, each of which is hereby incorporated by
reference in its entirety.
Claims
What is claimed is:
1. A method of classifying material, wherein a number of potential
classifications are available, the method comprising acts of: (A)
detecting x-rays fluoresced from the material; (B) detecting
optical emissions emitted from a plasma resulting from a
vaporization of a portion of the material; and (C) classifying the
material based on the detected x-rays and the detected optical
emissions, including acts of (1) reducing the number of potential
classifications by analyzing only a first one of two types of
emissions: the detected x-rays or the detected optical emissions;
and (2) selecting one of the reduced number of classifications by
analyzing only a second one of the two types of emissions that was
not analyzed in the act (C)(1); wherein the act (C)(1) includes
analyzing only the detected optical emissions and the act (C)(2)
includes analyzing only the detected x-rays.
2. A method of classifying a piece of material, comprising acts of:
(A) irradiating the piece with x-ray photons to cause the piece to
fluoresce x-rays; (B) detecting x-rays fluoresced from the piece;
(C) vaporizing a portion of the piece to produce a plasma that
emits optical emissions; (D) detecting the optical emissions
emitted from the piece; (E) classifying the piece based on the
detected x-rays and the detected optical emissions by first
reducing a number of potential classifications using only the
detected x-rays or the detected optical emissions and then
selecting a final classification from among the reduced number of
potential classifications using only whichever of the detected
x-rays or detected optical emissions was not used in reducing the
number of potential classifications; (F) conveying the piece into
an area in which two or more of the acts (A), (B), (C), (D) and (E)
are performed; (G) conveying the piece out of the area, wherein the
act (F) includes conveying the piece on a first conveyor, and the
act (G) includes conveying the piece on a second conveyor distinct
from the first conveyor.
3. The method of claim 2, further comprising an act of: (H) sorting
the piece based on the classification.
4. The method of claim 2, wherein the act (B) is performed while
the piece passes from the first conveyor to the second
conveyor.
5. The method of claim 2, wherein the act (D) is performed while
the piece passes from the first conveyor to the second
conveyor.
6. The method of claim 2, wherein the act (A) is performed while
the piece passes from the first conveyor to the second
conveyor.
7. The method of claim 2, wherein the act (C) is performed while
the piece passes from the first conveyor to the second
conveyor.
8. The method of claim 2, wherein act (C) includes vaporizing the
portion of the piece using a laser beam.
9. The method of claim 2, wherein act (C) includes vaporizing the
portion of the piece using an electrical discharge.
10. The method of claim 2, wherein a predetermined number of
potential classifications are available, and wherein the act (E)
includes acts of: (1) analyzing only the detected optical emissions
to reduce the predetermined number to a reduced number of potential
classifications; and (2) classifying the piece of material as one
of the reduced number of classifications based on the detected
x-rays.
11. The method of claim 10, wherein act (E)(1) includes determining
that a threshold percentage of the detected optical emissions were
emitted by one or more particular elements included within the
piece.
12. The method of claim 11, wherein at least one of the one or more
particular elements is a low-Z element.
13. The method of claim 12, wherein at least one of the one or more
particular elements is magnesium.
14. The method of claim 12, wherein at least one of the one or more
particular elements is silicon.
15. The method of claim 12, wherein at least one of the one or more
particular elements is carbon.
16. The method of claim 12, wherein at least one of the one or more
particular elements is aluminum.
17. The method of claim 10, wherein the reduced number of
classifications represent a number of alloys belonging to a same
alloy group.
18. The method of claim 17, wherein the alloy group is an aluminum
alloy group.
19. The method of claim 2, wherein a predetermined number of
potential classifications are available, and wherein the act (E)
includes acts of: (1) analyzing only the detected x-rays to reduce
the predetermined number to the reduced number of potential
classifications; and (2) classifying the piece of material as one
of the reduced number of classifications based on the detected
optical emissions.
20. The method of claim 2, wherein act (E) includes: (1) creating
one or more emissions spectra from the detected x-rays and detected
optical emissions; and (2) estimating peak values for one or more
regions of interest of the one or more spectra.
21. The method of claim 20, wherein act (E)(2) includes applying a
shape fitting function to data corresponding to the one or more
regions of interest.
22. The method of claim 2, wherein at least a portion of the
material is in liquid or molten form.
23. The method of claim 2, wherein at least a portion of the
material is in solid form.
24. The method of claim 2, wherein the material comprises a
plurality of pieces of material in solid form, and the acts (A)-(G)
are performed on the plurality of pieces.
25. The method of claim 2, wherein the act (E) comprises
identifying a contaminant in the material.
26. A method of classifying material in a moving stream of
materials, comprising acts of: (A) detecting x-rays fluoresced from
the material as the material moves; (B) detecting optical emissions
emitted from a plasma resulting from a vaporization of a portion of
the material as the material moves; and (C) classifying the
material based on the detected x-rays and/or the detected optical
emissions, including (1) creating one or more emissions spectra
from the detected x-rays and detected optical emissions; and (2)
estimating peak values for one or more regions of interest of the
one or more spectra, wherein (C) comprises reducing a number of
potential classifications of the material by analyzing only a first
one of the detected x-rays and the detected optical emissions, and
then selecting one of the reduced number of potential
classifications by considering only the type of emissions not
considered in reducing the number of potential classifications.
27. The method of claim 26, wherein the act (C)(2) includes
applying a shape-fitting function to data corresponding to the one
or more regions of interest.
28. The method of claim 26, further comprising: (D) based on the
classification, sorting the material by removing the material from
the stream to a location associated with the classification.
29. The method of claim 26, wherein at least a portion of the
material is in liquid or molten form.
30. The method of claim 26, wherein at least a portion of the
material is in solid form.
31. The method of claim 26, wherein the material comprises a
plurality of pieces of material in solid form, and the acts (A)-(C)
are performed on the plurality of pieces.
32. The method of claim 26, wherein the act (C) comprises
identifying a contaminant in the material.
33. A method of classifying material, the method comprising acts
of: (A) applying an electrical discharge to vaporize a portion of
the material to produce a plasma; (B) detecting optical emissions
emitted from the plasma; (C) detecting x-rays fluoresced from the
material; and (D) classifying the material based on the detected
x-rays and/or the detected optical emissions, wherein a number of
potential classifications are available, wherein the act (D)
comprises: (1) reducing the number of potential classifications by
analyzing only a first one of two types of emissions: the detected
x-rays or the detected optical emissions; and (2) selecting one of
the reduced number of classifications by analyzing only a second
one of the two types of emissions that was not analyzed in the act
(D)(1).
34. The method of claim 33 wherein the act (D) includes creating
one or more emissions spectra from the detected x-rays and detected
optical emissions and estimating peak values for one or more
regions of interest of the one or more spectra.
35. The method of claim 33, wherein the material is part of a
moving stream of materials, further comprising acts of: (E) based
on the classification, sorting the material by removing the
material from the stream to a location associated with the
classification, wherein the acts (A)-(D) are performed as the
material is moving.
36. The method of claim 33, wherein at least a portion of the
material is in liquid or molten form.
37. The method of claim 33, wherein at least a portion of the
material is in solid form.
38. The method of claim 33, wherein the material comprises a
plurality of pieces of material in solid form, and the acts (A)-(D)
are performed on the plurality of pieces.
39. The method of claim 33, wherein the act (D) comprises
identifying a contaminant in the material.
40. A method of automated sorting of material in a stream of
materials presented for sorting, comprising acts of: (A) detecting
x-rays fluoresced from the material as it moves; (B) detecting
optical emissions emitted from a plasma resulting from a
vaporization of a portion of the material as it moves; (C)
classifying the material based on the detected x-rays and the
detected optical emissions; and (D) based on the classification,
sorting the material by removing the material from the stream to a
location associated with the classification, wherein (C) comprises
determining a first classification based on the detected x-rays or
the detected optical emissions and then determining a second
classification based on the other of the detected x-rays or the
detected optical emissions not used to determine the first
classification.
41. The method of claim 40, wherein the act (A) comprises conveying
the material at a rate of at least 0.3 meter per second.
42. The method of claim 40, wherein the acts (A)-(D) are performed
on materials of varying shapes and sizes.
43. The method of claim 40, wherein the acts (A), (B) and (C) are
performed in less than one second.
44. The method of claim 40, wherein the act (C) comprises: (1)
creating one or more emissions spectra from the detected x-rays and
the detected optical emissions; and (2) estimating peak values for
one or more regions of interest of the one or more spectra.
45. The method of claim 40, wherein at least a portion of the
material is in liquid or molten form.
46. The method of claim 40, wherein at least a portion of the
material is in solid form.
47. The method of claim 40, wherein the material comprises a
plurality of pieces of material in solid form, and the acts (A)-(E)
are performed on the plurality of pieces.
48. The method of claim 40, wherein the act (C) comprises
identifying a contaminant in the material.
49. A method of classifying material, wherein a number of potential
classifications are available, the method comprising acts of: (A)
detecting x-rays fluoresced from the material; (B) detecting
optical emissions emitted from a plasma resulting from a
vaporization of a portion of the material; and (C) classifying the
material based on the detected x-rays and the detected optical
emissions, including acts of (1) reducing the number of potential
classifications by analyzing only a first one of two types of
emissions: the detected x-rays or the detected optical emissions;
and (2) selecting one of the reduced number of classifications by
analyzing only a second one of the two types of emissions that was
not analyzed in the act (C)(1); wherein the act (C)(1) includes
analyzing only the detected optical emissions and the act (C)(2)
includes analyzing only the detected x-rays, wherein (C) involves
use of immature emission spectra, and wherein (A)-(C)(2) is
performed in less than one second, wherein the method further
comprises automatically feeding multiple pieces of material
including the material onto a conveyor configured to convey the
material into an area in which (A)-(B) are performed and conveying
the material out of the area.
50. The method of claim 49, wherein (A)-(C)(2) is performed in less
than five hundred milliseconds.
51. The method of claim 49, wherein conveying the material into and
out of the area comprises conveying the material at a rate of at
least 0.3 meter per second.
52. The method of claim 51, wherein (A)-(B) are performed while the
material is being conveyed.
53. The method of claim 49, wherein sorting the material comprises
automatically discharging the material from a conveyor.
54. The method of claim 49, wherein the material has contaminants
on its surface.
55. The method of claim 49, further comprising conveying the
material from a first conveyor to a second conveyor separated by an
air gap, and wherein (A) and/or (B) is performed while the material
traverses the air gap.
56. The method of claim 55, wherein (A) comprises detecting the
x-rays from underneath the material as it traverses the air
gap.
57. The method of claim 49, further comprising collecting
transmitted x-rays through the material and wherein (C) comprises
classifying the material based on the transmitted x-rays.
58. The method of claim 49, further comprising creating one or more
emissions spectra from the detected x-rays and detected optical
emissions and estimating peak values for one or more regions of
interest of the one or more spectra.
59. The method of claim 49, wherein the method further comprises
irradiating the material with x-rays using an x-ray source
positioned beneath the material.
60. The method of claim 59, wherein the method further comprises
conveying the material, and wherein the material is irradiated with
x-rays while the material is conveyed and wherein (A) is performed
while the material is conveyed.
61. The method of claim 60, wherein the conveyor includes an
opening, and wherein irradiating the material with x-rays using an
x-ray source positioned beneath the material comprises irradiating
the material with x-rays through the opening.
62. The method of claim 61, wherein the conveyor is a mesh conveyor
comprising the opening, and wherein irradiating the material with
x-rays using an x-ray source positioned beneath the material
comprises irradiating the material with x-rays through the mesh
conveyor.
63. The method of claim 60, wherein the conveyor comprises a
window, and wherein irradiating the material with x-rays using an
x-ray source positioned beneath the material comprises irradiating
the material with x-rays through the window.
64. The method of claim 60, wherein conveying the material
comprises conveying the material from a first conveyor to a second
conveyor separated by an air gap, and wherein irradiating the
material with x-rays using an x-ray source positioned beneath the
material comprises irradiating the material as it traverses the air
gap.
65. The method of claim 60, wherein conveying the material
comprises conveying the material with a split conveyor belt,
wherein the split conveyor belt comprises first and second conveyor
belts arranged in parallel to each other and having an air gap
therebetween.
66. A method of classifying material, wherein a number of potential
classifications are available, the method comprising acts of: (A)
detecting x-rays fluoresced from the material; (B) detecting
optical emissions emitted from a plasma resulting from a
vaporization of a portion of the material; (C) detecting x-rays
transmitted through the material; and (D) classifying the material
based on the detected x-rays fluoresced from the material, the
x-rays transmitted through the material, and the optical emissions,
wherein (D) comprises (1) reducing the number of potential
classifications by considering a subset of results from (A), (B),
and (C); and (2) selecting one of the reduced number of
classifications by analyzing a different subset of results of (A),
(B), and (C).
67. The method of claim 66, wherein one or more of (A)-(C) are
performed from below the material.
68. The method of 66, further comprising: (E) irradiating the
material with x-rays; and (F) irradiating the material with an
optical source.
69. The method of claim 68, wherein one or more of (A), (B), (C),
(E), and (F) are performed from below the material.
70. The method of claim 69, further comprising conveying the
material.
71. The method of claim 70, wherein conveying the material
comprises conveying the material with a mesh conveyor.
72. The method of claim 70, wherein conveying the material
comprises conveying the material with a split conveyor belt,
wherein the split conveyor belt comprises first and second conveyor
belts arranged in parallel to each other and having an air gap
therebetween.
73. The method of claim 70, wherein conveying the material
comprises conveying the material on a conveyor having a window, and
wherein performing one or more of (A), (B), (C), (E), and (F) from
below the material comprises performing one or more of (A), (B),
(C), (E), and (F) through the window.
74. The method of claim 70, wherein conveying the material
comprises conveying the material from a first conveyor to a second
conveyor separated by an air gap, and wherein performing one or
more of (A), (B), (C), (E), and (F) from below the material
comprises performing one or more of (A), (B), (C), (E), and (F) as
the material traverses the air gap.
75. The method of claim 70, wherein (A) and (E) are performed from
below the material and wherein (B), (C) and (F) are performed from
above the material.
Description
BACKGROUND
Current worldwide environmental concerns have fueled an increase in
efforts to recycle used equipment and articles containing materials
that can be reused. Such efforts have produced new and improved
processes for sorting materials such as plastics, glasses, metals,
and metal alloys.
As used herein, a "material" may be a chemical element, a compound
or mixture of two or more chemical elements, or a compound or
mixture of a compound or mixture of chemical elements, or any
suitable combination thereof, wherein the complexity of a compound
or mixture may range from simple to complex. Types of materials
include organic materials, metals (ferrous and non-ferrous), metal
alloys, plastics, polymers, rubber, glasses, ceramics, fabrics,
other materials and any suitable combination thereof. As used
herein, "element" means a chemical element of the periodic table of
elements, including elements that may be discovered after the
filing date of this application.
Generally, methods for sorting pieces of materials involve
determining one or more properties, for example, one or more
physical and/or chemical properties, of each piece, and grouping
together pieces sharing a common property or properties. Such
properties may include color, hue, texture, weight, density,
transmissivity to light, sound, or other signals, and reaction to
stimuli such as various fields. Methods to determine these
properties include visual identification of a material by a person,
identification by the amount and/or wavelength of the light waves
emitted or transmitted (commonly referred to as optical emission
spectroscopy or OES), eddy-current separation, heavy-media plant
separation, and x-ray fluorescence (XRF) detection.
With respect to metals and metal alloys, today it is neither
technically nor commercially feasible to separate and recover many
of the non-ferrous metals that are manufactured into products and
discarded at the end of their useful life. In residential waste,
only aluminum cans are recycled to any significant degree.
Virtually none of the other non-ferrous materials in our
residential waste are recovered. Instead, they are disposed in
landfills. Further, in the U.S., small non-ferrous materials below
5/8 inches (.about.1.5 cm) in size are landfilled from nearly 200
automobile shredders.
Smaller-sized pieces of non-ferrous metals from automobile
shredders are not separated because their recovery is not
cost-effective. They can only be consolidated and shipped to larger
facilities for further processing. Mixed non-ferrous metals from
industrial processes are often disposed or junked because
hand-sorting and small-particle recovery technologies either do not
work well or are not cost-effective. Nearly 2 billion pounds of
valuable non-ferrous metals are discarded in landfills every year
in the U.S. alone. Worldwide, the amount of metal wasted is far
greater. If this metal could be economically recycled at high
volumes, the potential value generated is estimated to be in excess
of 1 billion dollars (U.S.) per year. Further, there are
approximately 200 waste-to-energy facilities, 200 automobile
shredders, and to thousands of metal scrap yards in the U.S. alone
that could benefit financially (and otherwise) from an improved
sorting system.
OES, mentioned above, is a known technique for sorting scrap metal,
for example, as described in U.S. Pat. No. 6,545,240 B2, titled
"Metal Scrap Sorting System" by Kumar, the entire contents of which
are hereby incorporated by reference. A known problem with OES
systems is that OES is not efficient at identifying a wide-range of
metals and, therefore, typically is calibrated for use on a
particular alloy group. For example, an OES system may be used to
identify aluminum alloys only or magnesium alloys only. Applicant's
understanding of the source of this problem is as follows. In order
to achieve accurate identification for different base metals of
alloys, known OES systems require that the calibration settings for
OES spectral identification be adjusted for each group. For
example, the calibration setting for an aluminum alloy is different
than the calibration settings for a nickel alloy. As used herein, a
"base metal" of an alloy is the metal having the largest percentage
of the mass of the constituent elements of the alloy.
In contrast, XRF spectroscopy is well-suited for classifying a
wide-range of metals, including the base metals of alloys. XRF
spectroscopy has long been a useful analytical tool in the
laboratory for classifying materials by identifying elements within
the material, both in academic environments and in industry. The
use of characteristic x-rays such as, for example, K-shell or
L-shell x-rays, fluoresced from elements in response to being
stimulated by x-rays, provides a method for positive identification
of elements and their relative amounts present in different
materials, such as metals and metal alloys. For example, radiation
striking matter causes the emission of characteristic K-shell
x-rays when a K-shell electron is knocked out of the K-shell by
incoming radiation and is then replaced by an outer shell electron.
The outer electron, in dropping to the K-shell energy state, emits
x-ray radiation characteristic of the atom.
The energy of emitted x-rays depends on the atomic number of the
fluorescing elements. Energy-resolving detectors can detect the
different energy levels at which x-rays are fluoresced, and
generate an x-ray signal from the detected x-rays. This x-ray
signal then may be used to build an energy spectrum of the detected
x-rays, and from the information, the element or elements which
produced the x-rays may be identified. X-rays are fluoresced from
an irradiated element and the detected radiation depends on the
solid angle subtended by the detector and any absorption of this
radiation prior to the radiation reaching the detector. The to
lower the energy of an x-ray, the shorter the distance it travels
before being absorbed by air. Thus, when detecting x-rays, the
amount of x-rays detected is a function of the intensity of x-rays
emitted, the energy level of the emitted x-rays, the emitted x-rays
absorbed in the transmission medium, the angles between the
fluoresced x-rays and the detector, and the distance between the
detector and the irradiated material.
Although x-ray spectroscopy is a useful analytical tool for
classifying materials, with current technology, the cost is high
per analysis, and the time required is typically several seconds to
minutes or hours. For example, some hand-held x-ray analyzers are
able to acquire an XRF spectrum from a piece of scrap metal in
approximately five to fifteen seconds, after which the user sorts
the piece of scrap metal by hand. There are bench-top XRF systems
that are capable of acquisition times within this range as well.
Because of these relatively long analysis times, scrap yard
identification of metals and alloys is primarily accomplished today
by trained sorters who visually examine each metal object one at a
time. Contamination is removed by shearing. A trained sorter
observes subtle characteristics of color, hue, texture, and density
to qualitatively assess the composition of the metal. Sometimes,
spark testing or chemical "litmus" testing aids in identification.
The process is slow and inaccurate, but is the most common method
in existence today for sorting scrap metal to upgrade its
value.
There have been disclosed a variety of systems and techniques for
classifying materials based on the XRF of the material. Some of
these systems involve hand-held or bench-top XRF detectors. These
types of systems are less accurate than laboratory analyzers, but
often give an accurate classification of the alloy in several
seconds. Other systems include serially conveying pieces of
material along a conveyor belt and irradiating each piece, in turn,
with x-rays. These x-rays cause each piece of material to fluoresce
x-rays at various energy levels, depending on the elements
contained in the piece. The fluoresced x-rays are detected, and the
piece of material is then classified based on the fluoresced
x-rays, and is automatically sorted in accordance with this
classification.
Such disclosed systems, however, have not been widely accepted
commercially because they require more than one second to detect
the x-rays and accurately classify the piece of material
accordingly, and they are expensive relative to the number of
objects identified per unit time.
An improved approach to sorting scrap metal and other materials is
disclosed in U.S. Pat. No. 6,266,390, titled "High Speed Materials
Sorting System Using XRF" by Sommer, Jr. et al. (hereinafter, "the
Sommer patent"), the entire contents of which are hereby
incorporated by reference. In the Sommer patent, XRF sensing is
applied to classify pieces of material as small as 1/4 inches,
which are conveyed in a singulated stream through a sensing region
at speeds as fast as 60 in/sec. to 120 in/sec. The Sommer patent
discloses a novel system that employs fast-sorting techniques,
algorithms and equipment to irradiate the pieces causing them to
fluoresce x-rays, detect the x-rays, classify the piece based on
the detected x-rays and sort the pieces off of the fast-moving
conveyor belt at speeds as fast as 10 pieces per second or
more.
A problem with known sorting systems, whether hand-held, bench-top,
or a system involving conveyor belts, is the difficulty of using
XRF spectroscopy to accurately classify pieces of material
containing elements with low atomic number (i.e., low-Z elements).
As used herein, a "low-Z element" is an element in the periodic
table of elements having an atomic number of less than 22, i.e.,
less than the atomic number of titanium. As used herein, a "high-Z
element" is an element in the periodic table of elements (including
elements added after the filing date of this application) having an
atomic number of 22 or greater, i.e., the atomic number of titanium
or greater. For example, detection of pieces containing aluminum,
which has an atomic number of 13, and other low-Z elements such as
silicon and magnesium, is difficult with XRF spectroscopy. The
problem is two-fold. First, the x-rays (even the x-rays of highest
energy--K-alpha x-rays) fluoresced from the low-Z elements are at
very low energy (e.g., approximately between 1-2 keV) such that
they are easily absorbed in air. Second, for a given amount of
x-rays (i.e., the x-rays from an x-ray source) irradiating a piece,
low-Z elements within the piece fluoresce less x-rays than high-Z
elements within the piece. The low-Z elements fluoresce less x-rays
because the low-Z elements have a sparser concentration of
electrons than the high-Z elements. Thus, for a given amount of
impacting x-rays, there is a lower probability of dislodging
electrons shells (i.e., energy levels) of low-Z elements than from
shells of high-Z elements.
FIG. 1 is a graph 100 illustrating values of the x-ray energy for
various common metals encountered in recycling. The energies for
three different types of x-rays, K.alpha., L.alpha., and L.beta.,
are shown in FIG. 3 (shown as Ka, La and Lb, respectively). K
x-rays are x-rays resulting from an electron of a K-shell of an
atom (the inner most shell) being expelled or knocked out of the
k-shell and being replaced by an electron from an outer shell
(e.g., L-Q). A K.alpha. x-ray is an x-ray resulting from when the
replacing electron is from the next closest outer shell, L, whereas
a K.beta. x-ray (not shown) is an x-ray resulting from when the
replacing electron is from the M-shell. L x-rays are x-rays
resulting from an electron of an L-shell of an atom (the next inner
most shell) being expelled or knocked out of the L-shell and being
replaced by an electron from an outer shell (e.g., M-Q). An
L.alpha. x-ray is an x-ray resulting from when the replacing
electron is from the next closest outer shell, M, whereas a K.beta.
x-ray is an x-ray resulting from when the replacing electron is
from the N-shell. K x-rays have a higher energy than L x-rays.
From FIG. 1, it can be seen that the energy and yield of fluoresced
x-rays is small for aluminum and magnesium compared to the other
metals. FIG. 1 also illustrates the percentage of x-rays, for
different energy levels, transmitted through air over various
distances without first being absorbed by air (these calculations
were determined by approximating the density of air to being equal
to that of nitrogen). Curve 102 represents the percentage of x-rays
transmitted a distance of 12.7 mm Curve 104 represents the
percentage of x-rays transmitted a distance of 25.4 mm, and curve
106 represents the percentage of x-rays transmitted a distance of
38.1 mm. As is illustrated by curves 102, 104, 106, the percentage
of x-rays transmitted without being absorbed by air increases as
the energy of the x-rays increases and as the distance
decreases.
One solution to the above problem, at least for sorting pieces of
material containing only low-Z elements, is sorting pieces of
material by "difference", i.e., by configuring a sorting system
such that pieces of material containing only low-Z elements are the
only pieces that are left on the conveyor belt after all other
pieces have been classified and sorted. For example, the pieces
containing only low-Z elements are sorted into a default bin. An
example of this technique is described in the Sommer patent. This
solution has some drawbacks. One drawback is that multiple low-Z
elements cannot be sorted separately using this technique, as all
pieces of material containing only low-Z elements are left on the
conveyor belt.
Another drawback to this technique is that pieces of material
containing both low-Z elements and high-Z elements may be
incorrectly classified and sorted because at high speeds x-rays
fluoresced by the high-Z elements may be the only fluoresced x-rays
that are detected. Consider the case of aluminum. Aluminum alloys
may have zinc and/or copper as an alloying agent, and some bronze
alloys may have copper as the primary metal with aluminum as an
alloying agent. Because an XRF sensor may be unable to detect
x-rays fluoresced by aluminum when an aluminum alloy is exposed to
x-rays for only a short time (e.g., in a high speed sorting
system), these alloys may be mistakenly identified as zinc, copper,
or brass (a copper alloy) and, consequently, may be mis-sorted,
thereby contaminating the sorted zinc and to copper pieces with
pieces of aluminum alloy containing zinc and copper.
A hand-held LIBS analyzer for identifying pieces of scrap metal
that contain one or more low-Z elements such as aluminum, magnesium
and silicon has been disclosed. However, such an analyzer would be
slow and cumbersome, requiring the operator to touch a piece of
scrap metal, hold the analyzer in position for several seconds,
read the output of the analyzer, and then manually sort the piece
of material by moving it into a sorting bin or other suitable
location. Further, such a hand-held analyzer would be useful only
for identifying that pieces of materials contain low-Z elements,
but not for classifying a broad range of materials, which may
contain high-Z and low-Z elements in any of a variety of
combinations.
SUMMARY
In an embodiment of the invention, a piece of material is
classified. X-rays fluoresced from the piece and optical emissions
emitted from the piece are detected. The piece is classified based
on at least one of: the detected x-rays, and the detected optical
emissions.
In another embodiment of the invention, a computer program is used
to control a computer to perform the method of the embodiment
described in the preceding paragraphs.
In another embodiment of the invention, a system for classifying a
piece of material is provided. The system includes a classification
module to receive x-ray fluorescence information representing
x-rays fluoresced from the piece, to receive optical emissions
information representing optical emissions emitted from the piece,
and to classify the piece based on at least one of the x-ray
fluorescence information and the optical emissions information.
In yet another embodiment, a system for classifying a piece of
material is provided. The system includes one or more inputs to
receive x-ray fluorescence information representing x-rays
fluoresced from the piece and optical emissions information
representing optical emissions emitted from the piece. The system
further includes means for classifying the piece based on at least
one of the x-ray fluorescence information and the optical emissions
information.
In yet another embodiment, a method of classifying a piece of
material is provided. The method comprises acts of: (A) detecting
x-rays fluoresced from the piece; (B) detecting optical emissions
emitted from the piece; and (C) classifying the piece based on at
least one of: the detected x-rays, and the detected optical
emissions. In one embodiment, a predetermined number of potential
classifications are available, and the act (C) includes acts of:
(1) analyzing to only the detected optical emissions to reduce the
predetermined number to a reduced number of potential
classifications; and (2) classifying the piece of material as one
of the reduced number of classifications based on the detected
x-rays.
In yet another embodiment a method of classifying a piece of
material is provided. The method comprises acts of: (A) detecting
x-rays fluoresced from the piece; (B) detecting optical emissions
emitted from the piece; and (C) classifying the piece based on at
least one of: the detected x-rays, and the detected optical
emissions. In one embodiment, a predetermined number of potential
classifications are available, and the act (C) includes acts of:
(1) analyzing only the detected x-rays to reduce the predetermined
number to a reduced number of potential classifications; and (2)
classifying the piece of material as one of the reduced number of
classifications based on the detected optical emissions.
Other advantages, novel features, and objects of the invention, and
aspects and embodiments thereof, will become apparent from the
following detailed description of the invention, including aspects
and embodiments thereof, when considered in conjunction with the
accompanying drawings, which are schematic and which are not
intended to be drawn to scale. In the figures, each identical or
nearly identical component that is illustrated in various figures
is represented by a single numeral. For purposes of clarity, not
every component is labeled in every figure, nor is every component
of each embodiment or aspect of the invention shown where
illustration is not necessary to allow those of ordinary skill in
the art to understand the invention.
BRIEF DESCRIPTION OF THE DRAWINGS
FIG. 1 is a graph illustrating values of x-ray energy for various
common metals encountered in recycling, and illustrating the
percent of x-rays of various energy levels that are transmitted for
various distances without being absorbed by air;
FIG. 2 is a block diagram illustrating an example of a system for
sorting pieces of material using multiple sources of stimulation,
according to one or more embodiments of the invention;
FIG. 3 is a block diagram illustrating an example of a system for
sorting pieces of material using multiple x-ray sources, according
to one or more embodiments of the invention;
FIG. 4 is a graph illustrating an optical emission spectrum
including the optical emission spectra of aluminum, silicon and
magnesium resulting from a spark discharge;
FIG. 5 is a graph illustrating an optical emission spectrum
including the optical emission spectra for aluminum, silicon and
magnesium along with several other metals;
FIG. 6 is a block diagram illustrating an example of a system for
sorting pieces of material using a combination of XRF spectroscopy
and OES, according to one or more embodiments of the invention;
FIG. 7 illustrates an example of a vaporizing and detecting unit
used as part of a material sorting system, according to one or more
embodiments of the invention;
FIG. 8 is a block diagram illustrating an example of a system for
sorting pieces of material using a combination of XRF spectroscopy
and spark discharge spectroscopy or arc discharge spectroscopy,
according to one or more embodiments of the invention;
FIG. 9 is a data flow diagram illustrating an example of a data
acquisition and processing module, according to one or more
embodiments of the invention;
FIG. 10 is a flow chart illustrating an example of a method of
sorting a piece of material using a plurality of sources of
stimulation, according to one or more embodiments of the
invention;
FIG. 11 is a flow chart illustrating an example of a method of
classifying a piece of material using by estimating peak values for
regions of interest, according to one or more embodiments of the
invention;
FIG. 12 is a block diagram illustrating an example of a computer
system which can be used for one or more embodiments of the
invention;
FIG. 13 is a block diagram illustrating an example of a memory
system which can be used for one or more embodiments of the
invention.
FIGS. 14A and 14B are a flow chart showing an illustrative
embodiment of a process of sorting pieces of material at high
speed; and
FIG. 15 is a flow chart showing an illustrative embodiment of a
process for classifying a piece of material based on the x-ray
fluorescence spectrum of the piece.
DETAILED DESCRIPTION
Described herein are systems and methods for classifying a piece of
material that includes one or more low-Z elements based on
emissions (e.g., photonic emissions) detected from the piece of
material. As used herein, classifying a piece of material that
contains one or more low-Z elements includes identifying one or
more low-Z elements within the piece of material. It should be
appreciated that, although the systems and method described herein
are described primarily in relation to classifying pieces of
materials including low-Z elements, the invention is not so
limited. The systems and methods described herein may be applied to
classifying a piece of material that does not include any low-Z
elements.
In one or more embodiments, both XRF spectroscopy and OES
techniques, for example, Laser-Induced Breakdown Spectroscopy
(LIBS), arc discharge spectroscopy (ADS) or spark discharge
spectroscopy (SDS) may be used to classify the piece of material.
In other embodiments, only XRF spectroscopy techniques may be
used.
As used herein, to "classify" a piece of material is to determine
(i.e., identify) a class of materials to which the piece of
material belongs. The classes (i.e., classification) of materials
are user-definable and not limited to any known classification of
materials. The classes may be defined by using appropriate
reference spectra and by programming the threshold values for these
spectra, for example, as is described in the Sommer patent and/or
as is described below in relation to the classification module 930
of FIG. 9 and Act 1010 of FIG. 10. The granularity of the classes
may range from very coarse to very fine. For example, the classes
may include: plastics, ceramics, glasses, metals and other
materials, where the granularity of such classes is relatively
coarse; different metals and metal alloys such as, for example,
zinc, copper, brass, chromeplate, and aluminum, where the
granularity of such classes is finer; or between specific grades of
steel (or another alloy group), where the granularity of such
classes is relatively fine. Thus, the classes may be configured
(e.g., within classification module 930) to distinguish between
materials of significantly different compositions such as, for
example, plastics and metal alloys, or to distinguish between
materials of almost identical composition such as, for example,
different grades of an alloy.
It should be appreciated that the methods and systems discussed
herein may be applied to accurately classify pieces of material for
which the composition is completely unknown before being
classified.
In one or more embodiments, a stream of pieces of material is moved
along a conveying system (e.g., one or more conveyor belts or other
means for conveying) into a stimulation and detection area. The
stream of materials may include a single singulated stream, a
plurality of singulated streams in parallel or a stream of pieces
of material randomly distributed on the one or more conveyor belts.
Each piece of material, in turn, is stimulated with first and
second stimuli, of a same or different type. This stimulation
causes the piece of to material to emit emissions, for example,
photons. Such photons may include at least one of x-rays (i.e.,
x-ray photons) and optical emissions (i.e., optical photons). These
emissions then are detected by one or more detectors of one or more
types. The piece of material is then classified using, for example,
a combination of appropriately configured hardware, software and/or
firmware, based on the detected emissions. The amount of time that
elapses from the first detection of the emissions until the piece
of material is classified may be less than one second. Indeed, it
may be shorter than that: less than five hundred milliseconds, or
even less than one hundred milliseconds, such as less than fifty
milliseconds. Ideally, it may be as low as ten milliseconds or
less.
Downstream from the stimulation and detection area, the piece may
be sorted (e.g., automatically) by removing it from the conveying
system at an appropriate location, for example, using an air jet
that ejects the piece of material into an appropriate sorting bin.
As used herein, to "sort" a piece of material means to cause the
piece to be physically grouped with other pieces of material. These
other pieces of material may include pieces classified in a same or
different class than the sorted piece depending on the desired
sort, as is described in more detail below. The piece of material
may be in continual motion (e.g., moving along the conveying
system) while the acts of stimulating, detecting, classifying and
sorting operations are performed or, alternatively, the piece may
be stationary at some point during the process, for example, while
the piece is being stimulated and emissions therefrom are being
detected.
In one or more embodiments, the raw materials for one or more
alloys may be collected by sorting pieces of material in a suitable
manner, for example, as is described below in relation to FIG.
9.
In one or more embodiments, the acts of conveying, stimulating,
detecting, classifying and sorting all may be performed
automatically, i.e., without human intervention. For example, a
conveying system, one or more sources of stimuli, one or more
emissions detectors, a classification module, a sorting apparatus
and other system components may be pre-configured to perform these
and other operations automatically.
In one or more embodiments, each piece of material may be
stimulated by x-rays that cause the piece to fluoresce x-rays, and
may be stimulated by another stimulus, for example, a laser beam or
electrical discharge, that causes the piece to emit optical
emissions. The resulting x-rays and optical emissions then may be
detected, and the piece of material classified based on the
detected x-rays and optical emissions. The detected optical
emissions may be useful in identifying low-Z elements within the
piece of material, so that the piece of to material can be
accurately classified even if it contains low-Z elements.
In one or more embodiments, each piece of material may be
stimulated by first x-rays of a first energy range and second
x-rays of a second energy range (e.g., a lower range than the first
energy range), causing the piece to fluoresce x-rays. In one or
more aspects of this embodiment, the second x-rays may have a
higher intensity (i.e., more x-ray energy may be transmitted per
unit time), possibly ten times, a hundred times, a thousand times
or even ten thousand times (or greater) more intense than the
intensity of the first x-rays. If the second x-rays have a higher
intensity, then a larger percentage of the x-rays stimulating the
piece are within the second energy range than if the intensities of
the first and second x-rays were the same. Consequently, a larger
percentage of the x-rays fluoresced from the piece of material are
within the second energy range (e.g., lower energy range) than
otherwise would be if the intensities were the same. As a result, a
larger number of the detected x-rays are within the second energy
range than would be otherwise. Thus, if the second energy range is
an energy range within which low-Z elements fluoresce, and the
second x-rays are of higher intensity than the first x-rays, then a
greater number of the x-rays fluoresced from these low-Z elements
are detected, so that pieces of material containing low-Z elements
can be classified more accurately.
In one or more embodiments, the conveying system includes two
conveyor belts, with an air gap in-between, over which pieces of
material are conveyed from one belt to the other. These one or more
belts may be configured to convey pieces of material at any of a
variety of speeds, which in one or more embodiments may be as fast
as eight feet per second or faster. These one or more belts may be
arranged in series, with a first belt having a higher surface area
than the second belt, such that pieces of material may fall from
the first belt onto the second belt. Alternatively, the two belts
may have a same surface height. In one or more embodiments, the
conveying system may include a single conveyor belt that is
transparent to the types of stimuli being used to stimulate the
pieces of material and/or to the types of emissions resulting from
such stimulation (e.g., XRF or optical emissions). Alternatively,
in a single belt embodiment, the single belt may include a
substantial open area through which stimuli and/or emissions may
pass. For example, the conveyor belt may be a mesh belt or another
type of belt that includes openings. Further, in such a single belt
embodiment, the single belt may include windows through which
stimuli and/or emissions may pass. Advantageously, such windows may
define the lower surface of the pieces of material as they are
stimulated.
Each piece of material may be stimulated while passing over one or
more sources of stimuli positioned beneath any of an air gap,
opening or window described above. Such openings, air gaps and
windows enable one or more emissions detectors and/or one or more
sources of stimuli to be placed in close proximity to the location
at which each piece is stimulated. For example, if a stimulus
(e.g., x-rays) causes the piece to fluoresce x-rays, an XRF
detector can be placed in close proximity to the location at which
the piece is stimulated, regardless of the size or shape of the
piece. Accordingly, the XRF detector detects more x-rays fluoresced
by low-Z elements before such x-rays are absorbed by air than would
be detected if the XRF detector is positioned further away.
Further, a laser can be placed at a location beneath the air gap
that is a relatively constant distance from the location at which
each piece of material passes. As a result, the laser does not have
to be re-focused for each piece of material that passes over the
air gap. It should be appreciated that the air gap, opening, or
window, depending upon the embodiment, defines a vertical position
of the lower surface of the pieces of materials being stimulated.
In the case of a two-belt embodiment, the surface heights and the
belt speeds of the two belts may be configured such that when a
piece of material is thrown or conveyed across the air gap, it
undergoes little change in its vertical position (i.e., in the Z
direction).
Another benefit of providing an air gap, window or open area is
that the one or more sources of stimuli can be positioned to
prevent stimulation of objects in the stimulation area other than
the piece of material. For example, if one of the stimulus sources
is an x-ray source, the x-ray source (e.g., an x-ray tube) may be
positioned close enough to the bottom surfaces of pieces being
irradiated to prevent components of the conveying system and system
components within the stimulation area from fluorescing x-rays that
may be detected by an x-ray detector.
In one or more embodiments, an x-ray absorption detector array, or
another suitable device, may be provided to determine the position
of a piece of material within a stimulation and detection area. The
x-ray absorption detector array may be positioned such that each
piece of material is conveyed between the x-ray detector and the
one or more x-ray sources. The x-ray absorption detector array can
detect when a piece of material passes between the one or more
x-ray sources and itself, based on the amount of x-rays that it
detects, thus providing positional information regarding the piece
of material being stimulated. This positional information can be
used for any of a variety of purposes, for example, to position one
or more other emissions detectors, to position one or more stimulus
sources, to assist in controlling a sorting apparatus, and for
other reasons.
In one or more embodiments, curve fitting techniques may be used in
classifying a piece of material. Using curve fitting techniques,
immature emissions spectra, built from emissions detected over a
relatively short period of time (as short as ten milliseconds or
less) can be used to accurately sort the piece of material. This
short detection time enables the amount of time that elapses from
the first detection of the emissions until the piece of material is
classified to be less than one second. Indeed, it may be shorter
than that: less than five hundred milliseconds, or even less than
one hundred milliseconds, such as less than fifty milliseconds.
Ideally, it may be as low as ten milliseconds or less.
Curve fitting techniques may be used to classify the piece of
material as follows. From the detected emissions, which may include
x-rays and/or optical emissions, one or more emissions spectra may
be determined. These emissions spectra may include an XRF spectrum
and/or an optical spectrum. The emissions from which the emission
spectrum are created may be detected over a relative brief period
of time, as short as ten milliseconds or less. Consequently, the
resulting emissions spectra may be immature. In other words, the
visual pattern of the histogram of the emission spectra is more
jagged than if the detection times for the spectra were longer,
which would produce a smoother, more mature histogram. From each of
the one or more spectra, predetermined regions of interest (ROI)
may be analyzed. The predetermined ROI may include one or more
ranges of energy levels in an XRF spectrum and/or one or more
ranges of wavelengths in an optical spectrum. These ROI may be
pre-selected to correspond to energy levels or wavelengths at which
certain elements fluoresce x-rays or emit optical photons,
respectively. For each predetermined ROI, a peak value for the ROI
may be estimated by applying a shaping function to the sub-spectra,
for example, to the number of counts detected within the ROI. Thus,
by applying a shaping function to each ROI, a peak value for a more
mature spectrum within the ROI is estimated using the less mature
spectrum actually detected for the ROI. The shaping function may be
any of a variety of known shaping functions, for example, a
Gaussian distribution function or a Poisson distribution function.
The peak values estimated for the predetermined ROI may be used to
classify the piece of material using any of a variety of
techniques, described in more detail below in relation to FIGS.
9-11. Classifying the piece of material may include comparing the
determined peak value of the piece of material to the peak values
of ROI for one or more reference materials, as is described in more
detail below.
It should be appreciated that, although the systems and methods
described herein are to described primarily in relation to
classifying pieces of material in solid state, the invention is not
so limited. The systems and methods described herein may be applied
to classifying a material having any of a range of physical states,
including, but not limited to a liquid, molten, gaseous or powdered
solid state, another state, and any suitable combination
thereof.
The systems and methods described herein may be applied to classify
and/or sort individual pieces having any of a variety of sizes as
small as a 1/4 inch in diameter or less. Even though the systems
and methods described herein are described primarily in relation to
sorting individual pieces of material of a singulated stream one at
a time, the systems and methods described herein are not limited
thereto. Such systems and methods may be used to stimulate and
detect emissions from a plurality of materials concurrently. For
example, as opposed to a singulated stream of materials being
conveyed along one or more conveyor belts in series, multiple
singulated streams may be conveyed in parallel. Each stream may be
a on a same belt or on different belts arranged in parallel.
Further, pieces may be randomly distributed on (e.g., across and
along) one or more conveyor belts. For example, the pieces of
material may include flakes, grindings, filings, chips and turnings
("small pieces") made of metal and/or one or more other materials.
Such small pieces are commonly found among scrap metals.
Accordingly, the systems and methods described herein may be used
to stimulate, and detect emissions from, a plurality of these small
pieces at the same time. In other words, a plurality of small
pieces may be treated as a single piece as opposed to each small
piece being considered individually. Accordingly, the plurality of
small pieces of material may be classified and sorted (e.g.,
ejected from the belt) together. It should be appreciated that a
plurality of larger pieces of material also may be treated as a
single piece of material.
Although the systems and methods described herein are described
primarily in relation to sorting pieces of material, such systems
and methods are not limited to that use. They may be used for other
applications, for example, identifying elements (e.g.,
contaminants) within a piece of material (e.g., a molten mass of
material) or determining the composition of a piece of
material.
The methods and systems disclosed herein may be applied to a
handheld system for classifying pieces of material. In such a
system, adjustments would have to be made for portability, but the
general methods described herein for stimulating, detecting,
building emission spectra and classifying pieces of material based
on those spectra may be used.
The function and advantage of these and other embodiments of the
present invention will be more fully understood from the examples
discussed below. The following examples to are intended to
facilitate an understanding of the invention and illustrate the
benefits of the present invention, but do not exemplify the full
scope of the invention.
EXAMPLES
FIG. 2 is a block diagram illustrating (very schematically) an
example of a material sorting system 200 according to one or more
embodiments of the invention. System 200 is merely an illustrative
embodiment of a system for sorting pieces of material using
multiple sources of stimulation. Such an illustrative embodiment is
not intended to limit the scope of the invention, as any of
numerous other implementations of a system for sorting pieces of
material using multiple sources of stimulation, for example,
variations of system 200, are possible and are intended to fall
within the scope of the invention.
A conveying system 220 conveys a singulated stream of pieces of
material 202 into a stimulation and detection area 204, which may
be an enclosed area, for example, a chamber. Although a singulated
stream of pieces is illustrated in FIG. 2, it should be appreciated
that in other embodiments, the pieces of materials may be conveyed
in parallel singulated streams or randomly-distributed streams. The
pieces of material may have been received by the conveying system
220 from any of a variety of sources, for example, a suitable
feeder (not shown). The stimulation and detection area 204 may
include any of first stimulus source 206, second stimulus source
208, first emissions detector 210, second emissions detector 212
and position detector 214.
The first and second stimulus sources 206 and 208 each may be any
of a variety of types of stimulus sources, for example, a laser, an
electrical discharge device, an x-ray source (e.g., an x-ray tube
or an isotope), another type of stimulus source, or any suitable
combination thereof. In one or more embodiments, the stimulus
sources 206 and 208 may be a same type of stimulus source. In other
embodiments, the stimulus sources may be of different type, as will
be described in more detail below. Each piece of material 202 that
enters the stimulation and detection area may be stimulated by the
first stimulus source 206 and the second stimulus source 208 (e.g.,
concurrently), producing first emissions and second emissions,
respectively, from the piece of material. Depending on the types of
the first and second stimulus sources, the first and second
emissions may be of any of a variety of types, for example, x-rays,
optical emissions, or any suitable combination thereof.
Each of the first and second emissions detectors 210 and 212 may be
any of a variety of types of detectors, for example, a fluoresced
x-ray photon detector (i.e., an x-ray detector or XRF detector), an
optical emissions collector, a color sensor, a shape sensor, a
surface texture sensor, or any suitable combination thereof. The
types of the first and second emissions detectors 210 and 212, and
whether a second emissions detector 212 is necessary, may depend on
the types of emissions from the pieces of material. In one or more
embodiments, if the emissions from the pieces of material (as a
result of being stimulated by the first and second sources 206 and
208) are a same type of emission, then only one emissions detector
of a first type may be used. More than one emissions detector of
the first type may be used if desired. For example, as will be
described below in more detail in relation to FIG. 3, in one or
more embodiments of the invention, the first and second stimulus
sources 206 and 208 are both x-ray sources that cause pieces of
material to fluoresce x-rays. In such embodiments, one or more
x-ray detectors are the only type of emissions detectors used to
detect the x-rays, as other types are not needed.
Position detection device 214 may be any of a variety of types of
position detection device, for example, a x-ray absorption detector
array, an image sensor, other types of detectors, or any suitable
combination thereof. In one or more embodiments of the invention,
the position detection device 214 may be used to determine a
position of the piece within the stimulation and detection area
204. For example, the position detection device may be operable to
determine the position of the piece of material in an x-y plane
with respect to the conveying system 220, where, as shown in FIG.
2, x represents the direction in which the piece is being conveyed
and y represents the direction perpendicular to the direction of
movement and parallel to a top surface of the conveying system. As
will be described in more detail below, this positional information
may be used to aim one or more stimulus sources and/or one or more
emission detectors, to produce and detect, respectively, emissions.
Further, this positioning information could be used, for example,
by data acquisition and processing module 216 and/or sorting
apparatus 218 to sort pieces of material.
Each piece of material 202 may be received in the stimulation and
detection area 204, and may be stimulated by stimuli from the first
and second stimulus sources 206 and 208. These stimuli cause the
pieces of material to emit emissions that are detected by the first
detector 210 and, if necessary or desired, by other detectors such
as a second detector 212.
One or more elements 206, 208, 210, 212 and/or 214 of stimulation
and detection area 204 may be connected to data acquisition and
processing module 216 by network 205. As used herein, a "network"
is a group of two or more components interconnected by one or more
segments of transmission media on which communications may be
exchanged between the components. Each segment may be any of a
plurality of types of transmission media, including one or more
electrical or optical wires or cables made of metal and/or optical
fiber, air (e.g., using wireless transmission over carrier waves)
or any combination of these transmission media. As used herein,
"plurality" means two or more. It should be appreciated that a
network may be as simple as two components connected by a single
wire, bus, wireless connection or other type of segment. Further,
it should be appreciated that when a network is illustrated in a
drawing of this application as being connected to an element in the
drawing, the connected element itself is considered part of the
network. Thus, the network 205 may be as simple as one or more
wires, data buses or wireless connections between the data
acquisition and processing module 216 and one or more components
residing within the stimulation and detection area 204.
The data acquisition and processing module 216 may receive
positioning information and emission information, and may issue
positioning instructions to one or more of the stimulus sources
and/or emissions detectors. Further, the data acquisition and
processing module 216 may issue one or more sorting instructions
across network 217 to sorting apparatus 218. Network 217 may be as
simple as a single network segment connecting data acquisition and
processing module 216 and sorting apparatus 218. It should be
appreciated that networks 205 and 217 may be combined into a single
network.
The sorting apparatus may be any of a variety of types of sorting
apparatus, for example, an air jet apparatus that includes one or
more air jets disposed along the path of conveying system 220. In
response to receiving a sorting instruction, the sorting apparatus
218 may be configured to activate one or more of the air jets such
that the one or more air jets emit a stream(s) of air that cause(s)
a piece of material to be ejected from the conveying system 222,
for example, into a sorting bin. Any of a variety of types of air
jets may be used, such as high-speed air valves from Mac
Industries. These valves supply the jets with air pressure at, for
example, 60-90 psi, with operating/closing times as low as 15 ms or
less. Other types of sorting apparatuses and techniques may be
used, such as robotically removing the pieces of materials from the
conveying system 222, pushing the piece of material from the
conveying system, or causing an opening in the belt from which a
piece of material may drop.
System 200 also may include a sorting bin that receives pieces of
material not ejected from the conveying system 220. For example,
such a sorting bin may be located at the end of conveying system
220. The data acquisition and processing module may not instruct
the sorting apparatus to eject a piece of material such that it
falls into such bin. Thus, a sorting bin may serve as a default
sorting bin into which unclassified pieces of material are dumped.
Alternatively, such a sorting bin may be used to receive one or
more classifications of pieces of material by deliberately not
assigning any of the other sorting bins that corresponds to an air
jet (or other ejecting means) to the one or more
classifications.
Depending upon the classifications of materials desired, multiple
classifications may be mapped to a single air jet (or other
ejection means) and sorting bin. In other words, there need not be
a one-to-one correlation between classifications and sorting bins.
For example, it may be commercially beneficial to sort copper and
brass into the same sorting bin. To accomplish this sort, when a
piece of material is classified as either copper or brass, the same
air jet may be activated to sort the copper or brass piece into the
same sorting bin. The contents of this sorting bin may, for
example, then be used to create a copper/brass alloy. This sorting
technique may be applied to produce any desired combination of
material pieces and element distribution. The mapping of
classifications may be programmed into the classification module
930 described below in relation to FIG. 9, to produce such desired
combinations. Thus, classifications may be mapped to sorting bins
so as to create the raw materials from which an alloy or other
combinations of materials may be created. Creating alloys in this
fashion is described below in more detail in relation to
classification module 930 of FIG. 9.
The conveying system 220 may have any of a variety of geometries,
materials of construction, and operating parameters, each of which
may be optimized, for example, depending upon types of materials
being sorted. The properties of materials to be sorted that may
influence the geometry, materials of construction and operating
parameters of the conveying system 220 include: size, density,
geometry, frictional properties and moisture content. The conveying
system 220 may include one or more conveying belts made from any of
a variety of manufacturers, for example, Dorner and QC Industries.
These one or more conveyor belts may be customized by the
manufacturer based on the desired geometry, materials of
construction and operating parameters. Each of the one or more
conveying belts may be made from any of a variety of materials,
including but not limited to: rubbers, polymers, metals and
cloths/fabrics. The one or more conveyor belts may be constructed
and arranged to include ridges, pockets, side walls, mesh, cleats,
joins and embedment, or any suitable combination thereof, and may
be made in various thicknesses and sizes.
In one or more embodiments of the invention, the conveying system
220 may be divided into multiple belts in series. For example, two
belts may be provided, where a first belt to conveys the pieces of
material into the stimulation and detection area 204 and a second
belt conveys the pieces of materials away from area 204. The second
belt may be positioned at a lower height than the first belt such
that the pieces of material 202 fall from the first belt onto the
second belt in the stimulation and detection area 204. Further, the
surface heights and the speeds of the belts may be configured such
that the pieces do not move around on the second belt after landing
on the second belt. In one or more embodiments, during conveyance
through the stimulation and detection area, each piece of material
may be slid across a window of material that allows x-rays and/or
light to pass through. Accordingly, an x-ray source and/or optical
stimulating device (e.g., laser) may be situated to irradiate
x-rays and/or light, respectively, through the window.
The conveyor belt (or part of a conveyor belt) downstream from the
stimulation and detection area 204 may be implemented as a circular
conveyor or carousel, and the air jets or other suitable removal
means may be arranged along the exterior or interior of the
circular conveyor. Further, the entire conveying system 220 may be
circular, where the pieces of material are fed onto the conveying
system 220, and the stimulation and detection area is located at a
point along the conveying system 220.
In one or more embodiments, gravity may be used to accelerate the
speed of the pieces of materials. For example, the conveying system
220 may convey pieces of material onto a surface that slopes
downward leading toward area 204. Further, at some point along the
path of conveyance, the pieces of materials may be dropped into
free fall, and be stimulated during free fall from a stimulus
source or sources located along the sides. The emissions could also
be detected during free fall from one or more detectors located
along the path of trajectory. Such an arrangement reduces
background radiation if an x-ray source is used; however, the
detection process becomes more complex. The location and speed of
each falling piece may need to be detected to properly time the
sorting process (constant speed cannot be assumed as in other
embodiments). Further, the inherent unstable nature of pieces
rolling down a slope or in free fall introduces a variable element
into the sorting process. The position detection device 214 can at
least assist in determining the position and speed of pieces in
such an embodiment.
The conveying system 220 may include one or more belts that may be
depressed or troughed in the center such that the pieces of
material gravitate to the center (in the y-direction) of the one or
more conveyor belts, such that they are aligned to pass directly
beneath or above one or more emissions detectors and/or source of
stimulus. Other techniques may be used to center pieces of material
on the belt. For example, a materials feeder may be configured to
do so.
Optionally, the pieces of material fed onto the conveying system
220 may be flattened with a flattening apparatus (not shown), for
example, a rolls crusher before being fed onto the conveying system
220. By flattening the piece of material, friable materials
adhering to the piece of material may be liberated. Further,
flattening a piece of material before feeding the piece onto the
conveying system improves sorting and classification of the pieces
of materials. For example, flattened pieces of material move less
on the conveying system, and do not roll as much as non-flattened
pieces. Consequently, the position of a piece of material can be
anticipated by the data acquisition and processing module 216.
Module 216 may be configured to control the sorting apparatus based
on this anticipation so that the piece is properly sorted by
sorting apparatus 218. Also, flattening the pieces of material
provides a larger surface area to irradiate, and from which to
detect x-rays. Consequently, the piece of material is bombarded
with, and fluoresces, more x-rays, resulting in a more complete XRF
spectrum being determined for the piece of material than otherwise
would have been determined. Further, the composition of the piece
of material is less influenced by surface contaminants because
during flattening fresh material surfaces are exposed, such that a
cleaner XRF spectrum is produced. Consequently, the spectrum
detected is more representative of the piece of material and not
other materials that may be adhering to the surface of the piece of
material.
Another benefit to flattening pieces of material prior to
stimulation is that flattening the piece of material provides a
more regular (i.e., smoother) surface on the piece of material.
Having a more regular surface allows the focusing of a laser or
other optical stimulating device to be more predictable, thus
making easier the focusing of the optical stimulating device for
each piece.
FIG. 3 is a block diagram illustrating an example of a system 300
for sorting pieces of material using two x-ray sources 306 and 308.
System 300 is merely an illustrative embodiment of a system for
sorting pieces of material using multiple x-ray sources. Such an
illustrative embodiment is not intended to limit the scope of the
invention, as any of numerous other implementations of a system for
sorting pieces of material using multiple x-ray sources, for
example, variations of system 300, are possible and are intended to
fall within the scope of the invention.
System 300 includes any of first x-ray source 306, second x-ray
source 308 and x-ray detector 310, all within stimulation and
detection area 304, which may be an enclosed area to such as an
x-ray chamber. It should be appreciated that additional x-ray
detectors and/or x-ray sources may be provided. If multiple x-ray
detectors are provided, each detector may be optimized to detect
x-rays having a particular characteristic, for example, x-rays
having an energy level within a particular range. For example, one
or more x-ray detectors may be an x-ray detector from Amptek (e.g.,
a Cadmium Telluride detector) configured to detect x-rays in
relatively high energy levels (e.g., greater than 10 keV), and one
more other x-ray detectors may be an x-ray detector from Rontec
operable to detect x-rays in relatively low energy levels (e.g.,
less than 25 keV). In an embodiment, four x-ray detectors may be
provided.
System 300 also includes any of networks 205 and 217, data
acquisition and processing module 216, sorting apparatus 218 and
conveying system 320. The conveying system 320 may include one or
more conveyor belts that convey pieces of material 202 into the
stimulation and detection area 300 (e.g., an x-ray chamber), where
the pieces of material are bombarded with irradiating x-rays 322
and 324 to produce fluoresced x-rays 326.
The first x-ray source 306 may produce irradiating x-rays 322 and
the second x-ray source 308 may produce irradiating x-rays 324.
Each x-ray source may be any of a variety of types of x-ray
sources. Each x-ray source may be configured to produce broadband
x-rays or monochromatic x-rays. For example, monochromatic x-rays
may be produced using an x-ray source that incorporates a
doubly-curved crystal (DCC) and one or more filters. For example,
one or more of the x-ray sources may include a DCC and filter
available from X-ray Optical Systems, Inc. Such an x-ray source
typically reduces the background radiation and scatter typically
caused by a broadband x-ray source in an x-ray chamber or other
enclosed area. Such a monochromatic x-ray source can be used to
create x-rays of high intensity at a predetermined energy
level.
The intensity of x-rays produced by each x-ray source is
proportional to the rate (i.e., counts per unit time) at which
x-rays are transmitted. The number of x-rays fluoresced from a
piece of material irradiated with x-rays 322 and 324 is a function
of the intensity and energy levels of the irradiating x-rays 322
and 324. Thus, when either of the x-ray sources 306, 308 produces
less intense x-rays, less x-rays are fluoresced from the piece of
material. Consequently, fluoresced x-rays 326 are detected from the
piece of material for a longer period of time than otherwise would
be necessary to produce an XRF spectrum with a strong enough image,
i.e., a recognizable spectral pattern.
Each x-ray source may be an isotope-based x-ray source, for
example, Cd.sup.129, Am.sup.241, Co.sup.57 and Fe.sup.55. Although
isotope-based sources provide monochromatic x-rays, which is
desirable in some circumstances, isotope-based sources do not
produce x-rays at intensities that can be produced by an x-ray
tube. Further, as described above, monochromatic x-rays can be
produced from an x-ray tube or other type of broadband x-ray source
by using a DCC or by other means.
Therefore, to increase the speed of detection and classification,
each of the first and second x-ray sources 306 and 38 may be an
x-ray tube, for example, a water-cooled Varien OEG-50 x-ray tube,
which may be powered by a power supply such as a Spellman RMP 300
power supply. Such an x-ray tube and power supply combination is
capable of operating at up to at least 300 watts at 30 kV. In an
embodiment, at least one of the x-ray tubes may be operated at
13-17 kV at levels in the range of 1-10 watts. In other
embodiments, at least one of the x-rays sources may be operated at
100 kV and at 17 mA. An x-ray tube is capable of producing x-rays
several orders of magnitude more intense than any commercially
available isotope-based x-ray source. This intensity is
particularly advantageous when the piece of material 202 being
stimulated and classified is relatively small, or when the one or
more x-ray sources is a relatively long distance away from the
piece of material 202, or when the piece of material 202 is a
relatively long distance away from the x-ray detector 310. Further,
an x-ray tube has the added advantage of being capable of being
turned off when not in use, in contrast to a radioactive
isotope.
Using an x-ray tube, or another comparable high-intensity
irradiation source, as at least one of the first and second x-ray
sources 306 and 308 causes massive amounts of x-rays to be present
in the stimulation and detection area 304, orders of magnitude more
than would be present if an isotope-based source were used. The
presence of this amount of x-rays causes problems with the
detection of x-rays by the x-ray detector 310 and the determination
of an accurate XRF spectrum. To address these problems, the
irradiation and detection of x-rays may be conditioned, for
example, as described in the Sommer patent. Such conditioning may
include any of: filtering and/or aiming (e.g., collimating) any
x-rays output by x-ray sources, filtering any x-rays detected by
x-ray detectors, aiming (e.g., collimating) the detection of x-rays
by any x-ray detector, making or lining components of the conveying
system (e.g., components of one or more conveyor belts) and/or
detection area (particularly if enclosed) with materials that do
not fluoresce x-rays within the energy range being considered in
classifying pieces of material; other conditioning techniques; and
any suitable combination thereof. For example, to prevent the x-ray
detector 310 from being flooded, one or both of the to first x-ray
and second x-ray sources 306 and 308 may be operated at low power
levels to produce relatively low-intensity radiation such as, for
example, at 13.5 V and 0.03 mA, given an x-ray power output of only
0.4 watts. It should be appreciated that these conditioning
techniques also may be employed in embodiments of the invention
that incorporate any of systems 200, 600, 700 and 800 described in
relation to FIGS. 2, 6, 7 and 8, respectively.
In one or more embodiments, the first irradiating x-rays 322
produced by the first x-ray source 306 are within a first energy
range, and the second irradiating x-rays 324 produced by the second
x-ray source are within a second energy range 308. For example, the
first x-ray source 306 may produce x-rays 322 spanning a relatively
full energy range, and the second x-ray source 306 may produce
second irradiating x-rays 324 limited to a narrower and lower
energy range (e.g., an energy range within which low-Z elements
fluoresce x-rays). By producing more x-rays within the lower energy
range, the likelihood of detection of the low-Z elements, for
example, aluminum, magnesium, silicon, etc., is increased. This
increased likelihood of detection results for the following
reasons. The more intense x-rays increase the likelihood that the
irradiating x-rays from the x-ray source will reach the piece of
material. Further, the higher intensity increases the likelihood
that the sparsely-spaced elections of low-Z elements of the piece
will be impacted and dislodged, as opposed to the irradiating
x-rays passing through the low-Z elements without impact. This is
analogous to spraying a fire hose as opposed to a garden hose at a
collection of sparsely-spaced objects. The stream of water from the
garden hose is far more likely to pass through the objects without
hitting them than the stream of water from the fire hose. Thus, the
fluoresced x-rays 326 include a higher number of x-rays fluoresced
from low-Z elements than otherwise would be fluoresced. As a
result, more x-rays fluoresced from low-Z elements reach x-ray
detector 310 without being absorbed in air. For example, the first
and second x-ray sources may be configured such that the first
irradiated x-rays 322 range in energy from 0 keV to 30 keV or
greater, and the second irradiated x-rays 324 have energies of 4.5
keV or lower. To produce x-rays of 4.5 keV or lower, the second
x-ray source 308 may be an x-ray tube having a Ti target of
K.alpha.=4.5 keV. Optionally, the second x-ray source 308 may be
operated at an extremely high output flux, thereby increasing the
count of irradiated x-rays 324, for example, by orders of magnitude
(e.g., by ten, one hundred, one thousand, ten thousand, or even
more). If the piece 202 being irradiated contains low-Z elements,
this increased amount of irradiated x-rays 324 having an energy of
4.5 keV or lower produces an increased number of fluoresced x-rays
326 from low-Z elements having an energy level 4.5 keV or less.
Thus, for pieces of material including a plurality of elements,
including one or more low-Z elements such as Si, Mg and Al, a
greater number of the fluoresced x-rays 326 are x-rays fluoresced
from the low-Z elements. Accordingly, due to the higher number of
low-Z x-rays, a greater number of low-Z x-rays reach the x-ray
detector 310 instead of being absorbed by air. Therefore, the
relative proportions of x-rays from low-Z and high-Z elements that
reach the x-ray detector 310 more accurately reflect the relative
proportions of low-Z and high-Z elements in the piece of material.
Consequently, the XRF spectrum determined from the fluoresced
x-rays 326 more accurately represents the proportion of low-Z
elements present in the piece of material, so that the piece of
material is more accurately classified.
The x-ray detector 310 may be any of a variety of types of x-ray
detector, for example, an Si-PIN diode detector, an Si(Li) diode
detector, a high-purity Ge diode detector, or other type of x-ray
detector. The x-ray detector may be equipped with a window
comprising one or more x-ray transparent materials (e.g.,
beryllium, another low-Z element or an organic material) such that
the window admits low-energy x-rays. In an embodiment, the x-ray
detector is an Amptech XR-100T with Si-PIN diode detector with
beryllium window. The use of an Si-PIN diode detector increases the
amount of fluoresced x-rays 326 that may be detected in a given
time (i.e., increases the count rate) by up to three times the
count rate or more of current commercially-available classification
and sorting systems.
Si-PIN, Si(Li) and Ge diode detectors all are capable of handling
high-intensity XRF without flooding, and have energy resolution of
0.25 keV or less. Si(Li) and high-purity Ge diode detectors are
capable of detecting x-ray energies in a range from less than 1 keV
to over 1,000 keV. Further, Si(Li) and high-purity Ge detectors
provide high x-ray throughput, as such detectors are capable of
counting rates in excess of 100,000 counts per second, which is
approximately ten times higher than the count rates achieved by
current commercially-available classification and sorting systems.
Further, Si(Li) and high-purity Ge detectors each provide about 50%
better resolution than current commercially-available x-ray
detectors used in state-of-the-art sorting systems. However, a
disadvantage of using Si(Li) or high-purity Ge detectors is that
they are cooled using liquid nitrogen.
It should be appreciated that an Si-PIN, Si(Li) or Ge diode
detector may be used as x-ray detector 310 with only a single x-ray
source and still provide higher counting rates and improved
resolution over the x-ray detectors used in current
commercially-available sorting systems.
Having described, in detail, embodiments of the invention in which
a plurality of x-ray sources are used to stimulate x-rays from a
piece, embodiments in which both fluoresced x-rays and emitted
optical emissions are used to classify and sort pieces of material
will now be described in more detail.
In one or more embodiments of the invention, OES may be used to
classify pieces of material containing low-Z elements, for example,
in combination with XRF spectroscopy. Any of a variety of types of
OES may be used, including, but not limited to, LIBS, ADS and SDS.
Using LIBS, a laser may generate a laser beam that vaporizes a
portion of the piece of material, producing a plasma that emits
optical emissions that are detected and analyzed to classify the
piece of material. Using ADS or SDS, described below in more
detail, an electrical discharge device may produce an electric
discharge that vaporizes a portion of the piece of material,
producing a plasma that emits optical emissions that are detected
and analyzed to classify the piece of material.
FIG. 4 is a graph 400 illustrating an optical emission spectrum
including the optical emission spectra of aluminum, silicon and
magnesium (silicon and magnesium being common alloying agents of
aluminum). Graph 400 does not represent an actual detected
spectrum, but a theoretical spectrum based on known data. Graph 400
represents the spectra that may result from vaporizing a piece of
material including aluminum, magnesium and silicon using a spark
discharge. The relative intensities would vary depending on the
relative amounts of each element in the piece. It should be
appreciated that the optical emission spectra of these same
elements when subjected to a laser beam, as opposed to a spark
discharge, should be very similar to those shown in FIG. 4. The
data used to create graph 400 may be found in the CRC Handbook of
Chemistry and Physics, data generated by the National Institute of
Standards and Technology (NIST), and other sources known to those
of skill in the art. As is shown in FIG. 4, aluminum has prominent
emission lines 402a, 402b, 402c and 402d. The emission lines are
clustered in two groups, a first group at 3082 .ANG. and 3092
.ANG., and a second group at 3944 .ANG. and 3962 .ANG., with the
second group having the more prominent spectral lines. The silicon
lines 404A-404C and the magnesium lines 406A-406E also are
prominent, albeit not as prominent as the aluminum lines. The
spectral lines of aluminum, magnesium and silicon are relatively
well separated. For pieces of material that only emit optical
photons from aluminum, magnesium and silicon within the range of
wavelengths shown in graph 400, this relatively good separation
should enable the optical emissions from the piece to be resolved
into an optical emission spectrum from which the presence and
relative amounts of aluminum, silicon and magnesium can be
determined. Thus, OES works well for specific alloys including only
aluminum, silicon and/or magnesium.
FIG. 5 is a graph 500 that shows an optical emission spectrum
including the optical emission spectra for aluminum, silicon and
magnesium along with several other metals, including manganese,
copper, zinc, nickel, chromium, lead, tin, titanium and iron, each
of which is often found among scrap metals. Analogous to graph 400,
graph 500 represents a theoretical spectrum based on known data. As
opposed to XRF spectra for metals, in which each metal can be
identified with a relatively few prominent spectral lines, FIG. 5
illustrates that the optical emissions spectra for metals is far
more complex. This complexity makes somewhat difficult the accurate
classification at high speeds of pieces of material including a
wide range of these metals. Analysis can be further complicated
because surface impurities such as dirt, grease, and oxides on the
pieces of material may contribute further spectra in response to
being stimulated. Accordingly, it may be desirable to only use OES
to identify and classify low-Z elements, while using XRF
spectroscopy to identify and classify relatively high-Z
elements.
FIG. 6 is a block diagram illustrating an example of a system 600
for classifying and sorting a piece of material using a combination
of XRF spectroscopy and OES. System 600, and system 800 described
below, are merely illustrative embodiments of a system for sorting
pieces of material using a combination of XRF and OES. Such
illustrative embodiments are not intended to limit the scope of the
invention, as any of numerous other implementations of a system for
sorting pieces of material using a combination of XRF and OES, for
example, variations of systems 600 and 800, are possible and are
intended to fall within the scope of the invention.
The system 600 may include any of a vaporizing device 608, an x-ray
source 606, an optical emissions collector 612, a fluoresced x-ray
detector 610 and a x-ray absorption detector array 614, which all
may be located within a stimulation and detection area 604, which
may be an enclosed area such as a chamber. The system 600 also may
include a conveying system that includes a first conveyor belt 602
and a second conveyor belt 621, networks 205 and 217, data
acquisition and processing module 216 and sorting apparatus
218.
Following path 623, the pieces of material 202 may be conveyed by
the first conveyor belt 620 into stimulation and detection area
604. Within area 604, the piece of material 202 may be launched
across an opening between belts 620 and 621, landing on belt 621
and proceeding out of area 604 to be sorted. The surface heights
and speeds of conveyor belts 620 and 621 may be configured such
that pieces of material land cleanly (i.e., does not bounce or move
around after landing) on belt 621. While in area 604, the piece of
material 202 may be stimulated by stimulus 609 from a vaporizing
device 604, producing optical emissions 626, and may be irradiated
with x-rays 622 from x-ray source 606, producing fluoresced x-rays
610. X-ray source 606 may be any of a variety of types of x-ray
source, for example, one of the first or second x-ray sources 306
and 308 described above in relation to FIG. 3. The fluoresced
x-rays 626 may be detected by a fluoresced x-ray detector 610,
which may be any of a variety of types of x-ray detectors, for
example, the x-ray detector 310 described above in relation to FIG.
3.
The optical emissions 626 result from the impact on the piece of
material 202 by stimulus 609 from vaporizing device 608. The
vaporizing device 608 may be any of a variety of types of
vaporizing devices, for example, a laser, an electrical discharge
(e.g., an arc discharge device or a spark discharge device),
another type of device, or any suitable combination thereof. Thus,
stimulus 609 may be any of a variety of type of stimulus, for
example, a laser beam or an electrical discharge.
It should be appreciated that FIG. 6 is just a schematic
representation of system 600. Accordingly, elements 606, 608, 610,
613 and 614 may be arranged and positioned in any of a variety of
configurations other than that shown in FIG. 6. For example, one or
more of the components 608, 612 and 614 shown above path 623 may be
located below path 623, and any of components 606 and 610 located
below path 623 may be located above path 623.
In an embodiment where the vaporizing device 608 is a laser or
other light source, the stimulus 609 may be focused at a certain
distance from vaporizing device 608. For example, the vaporizing
device 608 may be configured to focus stimulus 609 on each piece of
material 202 using known auto focus or sonar techniques. Because
each piece of material 202 may be of a different size and shape,
each piece of material 202 may be a different distance from
vaporizing device 608 as it passes between belts 620 and 621. In
one or more embodiments, the vaporizing device 608 and the optical
emissions collector 613 may be located beneath path 623. Locating
the vaporizing device 608 beneath path 623 provides a relatively
constant distance between the vaporizing device 608 and pieces 202
as they pass between belts 620 and 621. Accordingly, the vaporizing
device could be pre-set to focus at a constant distance as opposed
to being re-focused for each piece 202.
In embodiments where it is desired to know the position of the
piece of material in the x-y plane during its in-flight trajectory,
the x-ray absorption detector array 614 may be used as a position
detection device. It should be appreciated that any of a variety of
other types of to position detecting devices may be used, for
example, an image detector. The x-ray absorption detector array 614
may be positioned above the piece's trajectory path 623 for
monitoring x-rays 627 emitted from the x-ray source 606.
Alternatively, the x-ray absorption detector array may be located
below the path, for example, if an x-ray source is located above
the path. As a piece passes between the detector 614 and the source
606, the x-ray absorption detector array 614 may detect when a
front edge of a piece 202 passes between x-ray source 606 and
detector array 614. Further, the detector array 614 may detect the
position of the piece in the x-y plane. The detector array 614
detects decreases in the amount of detected x-rays 627 at different
locations on the bottom x-y face of the detector array 614. In
other words, the passing piece 202 casts a sort of x-ray "shadow"
on the bottom x-y face of the detector array 614. The x-ray
absorption detector array 614 may send this transmitted x-ray
information over network 205 to data acquisition and processing
module 216. Module 216 then may analyze the data and determine the
position of the piece in the x-y plane.
This x-y positional information may be used to control operation of
the optical emissions collector 612 to aim it at the location at
which the luminous plasma is formed on the piece's surface, from
which the optical emissions 626 are detected. Further, the
detection by detector array 614 of the leading edge of piece 202
passing between detector array 614 and x-ray source 606 may be used
to initiate a laser or other vaporizing device 608 to generate a
laser beam pulse to stimulate the piece. This information also may
be used to trigger the aiming of the laser beam pulse and/or
emissions collector 612.
In one or more embodiments, system 600 may include a means for
aligning pieces 202 along the approximate center of belt 620 in the
y-direction or some other predetermined location in the
y-direction. Aligning the pieces of material ensures that each
piece is conveyed along belt 620 at a predefined position along the
y-direction, and therefore launches across the air gap at a
predetermined location along the y-direction. Aligning pieces in
this fashion obviates the need for a position detection device such
as the x-ray absorption detection array 614. For example, system
600 may include a materials feeder that feeds each piece of
material 202 onto belt 620 at a predefined position in the
y-direction.
The optical emissions collector 612 may be any of a variety of
types of optical emissions collectors. The collector 612 may
include one or more light-collection lenses, which serve to collect
the optical emissions 626 on one or more fiber optic strands. These
fiber optic strands may be part of a fiber optics cable that passes
the collected optical emissions through network 205 to data
acquisition and processing module 216. As described in more detail
to below in relation to FIG. 7, in one or more embodiments, the
fiber optic cable that carries the collected optical emissions may
also include one or more fiber optic strands that delivers the
laser beam pulse that stimulates the piece 202.
As illustrated in FIGS. 6 and 7, in one or more embodiments, the
pieces of material are launched (i.e., passed through the air) from
conveyor belt 620 to conveyor belt 621. Passing a piece of material
202 from the first belt 620 to the second belt 621 allows the x-ray
source 606 and the fluoresced x-ray detector 610 to be disposed
relatively close to the piece of material 202 being stimulated.
This relatively close spacing enables more x-rays 622 emitted from
the x-ray source to reach the piece 202 before being absorbed in
air, particularly x-rays fluorescent from low-Z elements. Further,
the fluoresced x-ray detector 610 can detect more fluoresced x-rays
626 before the fluoresced x-rays are absorbed in air, particularly
x-rays fluorescent from low-Z elements. Another advantage of using
two-belts in this fashion is that x-rays from the x-ray source 606
may be collimated and aimed so that they intersect the piece's
trajectory and pass into the space above the pieces trajectory. In
this space above the trajectory, the x-rays may be absorbed by air
or by an x-ray chamber or other enclosure that may enclose area
604. Such absorption reduces an amount of background radiation that
otherwise may be present if the stimulation sources and emissions
detectors are located above the stimulation location.
Further, as described above, such a two-belt system enables any of
the vaporizing device 608 (e.g., a laser and/or other optics) and
the optical emissions collector 612 to be placed beneath path 623,
thereby providing a relative constant distance between these
devices and pieces being stimulated. Accordingly, the need to
re-focus the vaporizing device 608 and/or the optical emissions
detector 612 for each piece may be obviated.
It should be appreciated that the system 600 is not limited to the
two-belt embodiment illustrated in FIG. 6. The conveying system of
system 600 may have any of a plurality of other suitable
configurations, such as those described above. For example, the
conveyor system may include a single belt that includes windows
and/or open areas (e.g., mesh). Further, the conveyor system may
include two belts having a same surface height, where the distance
between the belts is configured to be too small to allow a piece to
fall between. These two belts also may be configured to prevent a
piece from being jostled during transition between the two
belts.
It should be appreciated that although the two-belt system is
described in relation to using a combination of XRF spectroscopy
and OES as shown in FIG. 4, the use of a two-belt system is not
limited thereto. Such a two-belt system may be used even if there
is only one to stimulus source, for example, an x-ray source, or
only one emissions detector, for example, a fluoresced x-ray
detector. Such embodiments still would have the above-described
benefits resulting from being able to place the x-ray source and
the fluoresced x-ray detector at a relatively close proximity to
the piece of material being irradiated.
In one or more embodiments, the vaporizing device 608 and the
optical emissions collector 612 may be integrated within a same
vaporizing and detecting unit 613, for example, when a laser is
used as the vaporizing device.
FIG. 7 illustrates an example of a vaporizing and detecting unit
613 used as part of system 600. Vaporizing and detecting unit 413
is merely an illustrative embodiment of a vaporizing and detecting
unit. Such an illustrative embodiment is not intended to limit the
scope of the invention, as any of numerous other implementations of
a vaporizing and detecting unit, for example, variations of unit
413, are possible and are intended to fall within the scope of the
invention.
A laser 702 emits a laser beam pulse (i.e., a pulse of light) that
is reflected off a first dichroic mirror 704 and then reflected off
a second dichroic mirror 706. The light reflected from second
dichroic mirror 706 is then focused by lens 708 on a fiber optic
cap with a pinhole 710, which is connected to fiber optic cable
712. The light passes through fiber optic cable 712 and impacts a
lens 714 that produces the light that impacts the piece of material
202.
As indicated by the arrows throughout FIG. 7, the photons emitted
from the piece of material 202 then may be passed back through many
of the same components through which the light of the laser beam
passed before hitting the piece of material. Thus, fiber optics
cable 712 may include one or more strands that transmit the light
that impacts the piece of material 202 and one or more strands that
transmit the optical emissions emitted from the piece. Accordingly,
the emitted photons pass back through lens 714, through fiber
optics cable 712, through lens 708 and into lens 716. Lens 716
focuses the emitted photons onto a fiber optic cable 718, which
leads to data acquisition and processing module 216. It should be
appreciated that other embodiments of a vaporizing and detecting
unit may be used.
The vaporizing device 608 of FIG. 6 and/or the laser 702 may be
configured to generate multiple pulses of light with each piece of
material. For example, the first one or more pulses may be used to
vaporize surface contaminants (e.g., oxides) from the surface of
the piece being eradiated. After the service contaminants have been
cleared by the first one or more pulses, the last pulse may be used
to vaporize a portion of the piece of material to produce the
optical emissions on which the classification on which the piece is
based. Accordingly, system 600 may include control circuitry
control the timing of the detection of optical emissions to
coincide with the pulse that vaporizes a portion of the piece of
material, as opposed to mere surface contaminants on the piece of
material. Such control logic may reside within the data acquisition
and processing module 216, within the vaporizing and detecting unit
413, within another component, or may be shared between one or more
components of system 600.
FIG. 8 is a block diagram illustrating an example of a system 800
for classifying and sorting pieces of material 202 using XRF
spectroscopy and Arc Discharge Spectroscopy (ADS). System 800
includes several of the same components described above in relation
to FIG. 6. Instead of having a vaporizing device 608, for example,
a laser, system 800 includes an arc discharge device which includes
a power source 708 and electrodes 711 and 713. Power source 708 is
enabled to build up a charge between nodes 711 and 713. When a
piece 202 is not present between electrodes 711 and 713, the charge
remains on the electrodes because the air between the electrodes
serves as a dielectric. When a piece 202 passes between electrodes
711 and 713, a conductive path is created between the electrodes
causing electric discharge 715, 717 to vaporize a portion of piece
202. The vaporized portion becomes a plasma that emits optical
emissions 626.
In one or more other embodiments, spark discharge spectroscopy
(SDS) may be used instead of ADS. In contrast to ADS, in SDS a
spark is continually present between electrodes 711 and 713 (e.g.,
similar to a welding gun). The spark vaporizes a portion of piece
202 as it passes on the producing plasma which emits the optical
emissions 626. SDS, which often is used in a laboratory
environment, typically requires operation in less than an
atmosphere of pressure, for example in Argon. Further, SDS
typically is slower in classifying materials than ADS. Accordingly,
it may be desirable to use ADS over SDS.
FIG. 9 is a data flow diagram illustrating an example of the data
acquisition and processing module 216. The data acquisition and
processing module 216 may include any of positioning module 914,
user interface 916, spectrum acquisition module 918, classification
module 930 and sorting interface 932. The positioning module 914
may receiving positioning information 904, for example, from
position detection device 214. In an embodiment, the positioning
information 904 includes transmitted x-ray information 906, which
may be received from x-ray absorption detector array 614. The
positioning module 914 analyzes the positioning information 904 and
generates positioning instructions 902. Positioning instructions
902 may be sent to one or more components within the detection
area, for to example, a vaporizing device such as a laser and one
or more optical emissions collectors (e.g., 310 or 610).
Positioning instructions 902 may be used by the vaporizing device
to aim its stimulus at pieces of material. Optical emissions
collectors may use instructions 902 to aim their detection of
emissions from the piece 202, as described above in relation to
FIG. 6.
Further, the positioning module may provide information to the
sorting interface 932 based on the positioning information 904, and
the sorting interface may use this information to time sorting
instructions 942 for the sorting apparatus 944.
The spectra acquisition module 918 may receive emission information
908 from one or more emission detectors. This emission information
may include any of fluoresced x-rays information 910, optical
photon information 912 and other types of emissions information.
The spectra acquisition module may include an x-ray spectrum
acquisition module 920 for acquiring and processing the fluoresced
x-rays information 910 to produce XRF spectrum 926. The x-ray
spectrum acquisition module may include amplification logic to
amplify the fluoresced x-rays information 910 (e.g., x-ray pulses
received from an x-ray detector) into an amplified signal. The
spectrum acquisition module may include a multi-channel analyzer,
for example, the Amptech MCA 5000 acquisition card and software,
which has 2048 channels for dispersing x-rays into a discrete
energy spectrum with 2048 energy levels. In other embodiments, the
spectrum acquisition module may include a multi-channel analyzer
which has 1024 channels (or even less) for dispersing x-rays into a
discrete energy spectrum. The multi-channel analyzer may convert
the amplified analog signal into one or more digital signals
representing the XRF spectrum 926. The determined XRF spectrum 926
may be sent to classification module 930.
The spectrum acquisition module 918 also may include an optical
spectrum acquisition module 922, which may receive optical photon
information 912 and produce an optical spectrum 928. The optical
photon information 912 may be received from optical emissions
collector 412 or a similar component. The optical spectrum
acquisition module 922 may be any of a variety of types, for
example, an OES spectrometer.
It should be appreciated that each of x-ray spectrum acquisition
module 920 and optical spectrum acquisition module 922 may be
discrete components separate from one another and separate from the
data acquisition and processing module 216. In such an embodiment,
each device may be connected to the data acquisition of processing
module 216 by one or more network segments, for example, a wire,
cable or wireless connection.
The spectrum information 924, which may include any of XRF spectrum
926 and optical spectrum 928, is sent to classification module 930.
Classification module 930 may employ classification techniques, and
may be configured to implement any of Acts 1104-1110, described
below in relation to Act 1100. The classification module 930 may
compare the spectrum information 924 to emissions information 936
stored in materials database 934, which may reside on a same or
different device than classification module 930. The emissions
information 936 may include XRF information 938 and optical
information 940. The XRF information 938 may include a library of
reference spectra and/or a reference ROI vectors. The optical
information 940 may include a library of optical spectra and/or
reference ROI vectors. By comparing the spectrum information 924 to
the emissions information 936, the classification module may
determine a best match for the piece of material, or that there is
no match, and provide the appropriate information to the sorting
interface 932. The sorting interface 932 then may provide the
sorting instructions 942 to the sorting apparatus 944 in accordance
with the classification.
The classification module 930 may be configured to classify
materials using any of a plurality of types of techniques, for
example, as described in the Sommer patent in relation to step 59
in FIGS. 2a, 2b, and 6 of that patent, and described more fully at
the end of the present specification in relation to FIGS. 14A, 14B,
and 15.
In one or more embodiments, the XRF information 938 and the optical
information 940 are not separated collections of information, but
are one integral collection of information. For example, for a
given reference material, a reference spectra and/or reference ROI
vectors may include both optical and XRF information.
In one or more embodiments, the classification module 930 may be
configured to use the sorting bins to create alloys. For example,
classifications may be mapped to sorting bins to collect the raw
materials from which an alloy or other combinations of materials
may be created. The classification module 930 may be configured
(e.g., programmed) with the percentage composition of constituent
elements of alloys or other compound materials. Each alloy or
compound material may be mapped to a particular sorting bin. The
classification module 930 may be configured to instruct the sorting
apparatus (e.g., through a sorting interface 932) to sort pieces of
material containing one or more of the constituent elements into
the appropriate bin. The percentages of each constituent sorted
into a sorting bin may be monitored. For example, for each sorting
bin, the classification module 930 may ensure that the sorting bin
has the appropriate percentages of each constituent element when
the sorting process is complete and/or when the sorting bin is
full. To ensure that the proper percentages of elements are sorted
into each bin, the system 200 may include means for determining the
mass and/or size of each piece of material, for example, using an
image sensor, a weight sensor, an x-ray absorption detector array,
other devices, or any suitable combination thereof. Using its
knowledge of the mass of each piece of material and the piece's
determined classification, the classification module 930 can
control over time the percentage amounts of the elements sorted
into each bin.
The user interface 916 provides an interface between a human user
and the classification module, enabling communication between the
user and the classification module. The user interface 916 may be
an application or part of an application (i.e., a set of
computer-readable instructions) in communication with any of a
variety of types of user devices, including a display screen, a
mouse, a keyboard, a keypad, a track ball, a microphone (e.g., to
be used in conjunction with a voice recognition system), a speaker,
a touch screen, a game controller (e.g., a joystick), other user
devices and any suitable combination thereof. The user interface
916 may be configured to provide a user interface display on a
display device, for example, any of the user interface displays
illustrated in FIGS. 7 and 8 of the Sommer patent in the manner
described in the Sommer patent.
In one or more embodiments, no optical photon information 912
and/or positioning information 904 may be received by module 216.
In such embodiments, module 216 may not include optical spectrum
acquisition 922 and/or positioning module 914. Alternatively, these
components may be disabled, turned off or not used.
Data and acquisition module 216, and components thereof may be
implemented using software (e.g., C, C#, C++, Java, or a
combination thereof), hardware (e.g., one or more
application-specific integrated circuits), firmware (e.g.,
electrically-programmed memory) or any combination thereof. One or
more of the components of module 216 may reside on a single device,
or one or more components may reside on separate, discrete device.
Further, each component may be distributed across multiple devices,
and one or more of the devices may be interconnected.
Further, on each of the one or more devices that include one or
more components of module 216, each of the components may reside in
one or more locations on the device. For example, different
portions of the components 914, 916, 930 and 932 may reside in
different areas of memory (e.g., RAM, ROM, disk, etc.) on the
device. Each of such one or more devices may include, among other
components, a plurality of known components such as one to or more
processors, a memory system, a disk storage system, one or more
network interfaces, and one or more busses or other internal
communication links interconnecting the various components.
Module 216 may be implemented on a computer system described below
in relation to FIGS. 12 and 13.
Module 216 is merely an illustrative embodiment of a module for
acquiring emissions information and classifying pieces of material
based on such information. Such an illustrative embodiment is not
intended to limit the scope of the invention, as any of numerous
other implementations of a module for acquiring emissions
information and classifying pieces of material based on such
information, for example, variations of module 216, are possible
and are intended to fall within the scope of the invention.
Those of skill in the art should appreciate that the various
settings and parameters of the components of systems 200, 300, 600,
700. 800 and 900, including data acquisition and processing module
and its components, may be customized, optimized and reconfigured
over time based on the types of materials being sorted, the desired
sorting results, the type of equipment being used, empirical
results from previous sorts, data that becomes available and other
factors.
FIG. 10 is a flow chart illustrating an example of a method 1000
for classifying and sorting a piece of material using a plurality
of sources of stimulation.
In Act 1012, the piece may be sorted based on the classification,
for example, by activating an air jet or other mechanism for
removing a piece of material from the conveying system into an
appropriate location, for example, a sorting bin. Any of a variety
of techniques may be used to sort based on the classification, for
example, using any of the techniques described above.
In Act 1006, which may be performed concurrently to performance of
Act 1004, the piece is stimulated with a second stimulus, producing
second emissions. This second stimulus also may be any of a variety
of types of stimuli. Either of the first or second stimulus may be
produced by one of first stimulus source 206, second stimulus
source 208, first x-ray source 306, second x-ray source 308, x-ray
source 406 or vaporizing device 408, described above in relation to
FIGS. 2, 3 and 6-8.
In one or more embodiments, the first stimulus and the second
stimulus are of the same type, for example, x-rays. In other
embodiments, the first stimulus and the second stimulus may be
different types of stimuli. In an embodiment in which the first
stimulus and the second stimulus are both x-rays, each stimulus may
emit x-rays within different ranges, for example, as described
above. Further, one of the first or second stimulus may be more
intense (i.e., have a higher count rate) than the other stimulus,
for example, as described above.
In Act 1008, the first and second emissions are detected. It should
be appreciated that act 1008 or portions thereof may occur
concurrently with the performance of either of Acts 1004 or 1006.
Act 1008 may be performed by a single detector if the first and
second emissions or of a same type, for example, the first detector
210 of FIG. 2. Alternatively, one or more emissions detectors may
be used to detect the first and second emissions even if they are
of the same type. Alternatively, if the first and second emissions
are of different types, than a plurality of emissions detectors,
for example, fluoresced x-ray detector 410 and optical emissions
collector 413 described above in relation to FIG. 4, may be used to
detect the first and second emissions.
In Act 1010, the piece may be classified based on the detected
first and second emissions. For example, as described above in
relation to FIG. 9, spectrum information 924, which may include XRF
spectrum 926, an optical spectrum 928 or combination thereof, may
be received. Emissions information (e.g., information 936), which
may be stored in a database (e.g., materials database 934) may be
used to classify the piece of material. The piece may be classified
using any of a plurality of types of techniques, for example, as
described below in relation to FIG. 11, or as described in the
Sommer patent in relation to step 59 with reference to FIGS. 2a, 2b
and 6.
In Act 1012, the piece may be sorted based on the classification,
for example, for activating an air jet or other mechanism for
removing a piece of material from the conveying system into an
appropriate location, for example, a sorting bin. Any of a variety
of techniques may be used to sort based on the classification, for
example, using any of the techniques described above.
FIG. 11 is a flow chart illustrating an example of a method 1100 of
classifying a piece of material by estimating peak values for
regions of interest.
In Act 1102, one or more spectra may be built based on the detected
first and second emissions. For example, if the first and second
emissions are both x-rays, then a single x-ray spectrum 926 may be
generated by x-ray spectrum acquisition module 920. Alternatively,
if the first and second emissions include x-rays and optical
emissions, then x-ray spectrum acquisition module 920 may build XRF
spectrum 926, and optical spectrum acquisition module 922 may build
optical spectrum 928. Further, a single spectrum may be built that
includes both XRF and optical emissions data.
In Act 1104, a region of interest (ROI) vector may be determined
for each of the one or more spectra. Although a determined spectra
may include discrete energy counts spanning a wide range of energy
levels and/or wavelengths, it may be that only certain energy
levels or wavelengths are of interest in classifying a piece of
material. Such energy levels and/or wavelengths may serve to
distinguish classes of materials from one another. However, even
though the specific energy levels and wavelengths at which elements
produce emissions can be used to distinguish classes of materials,
the equipment used to capture emission spectra (e.g., XRF
detectors, optical emissions collectors, and XRF and optical
acquisition modules) are imperfect devices. Thus, the captured
emissions spectra may not perfectly reflect the energy levels and
wavelengths of the emissions that were actually emitted from a
piece of material. For example, although an element (e.g.,
titanium) may fluoresce x-rays at a specific energy level (e.g.,
4.51 keV), an XRF detector may only have a resolution of 0.25 keV.
Further, although the XRF detectors may detect a peak intensity at
4.50 keV for this element, the XRF detector also detects XRF at
other energy levels in a distribution pattern around 4.50 keV.
An ROI for a particular element may be defined to represent a range
of energy levels (or wavelengths) centered at the peak energy level
(or peak wavelength) at which an element fluoresces x-rays (or
emits optical photos). Pieces of material may be classified based
on emissions characteristics within the ROI, for example, the
number of energy counts detected within the ROI over a period of
time.
The ROI vector may include a plurality of values, where each value
represents one of the ROI for a spectrum. For example, each value
may represent a number of counts detected within the region of
interest. For example, if the ROI spans from 7.25 keV to 7.75 keV,
then the value representing that ROI in the ROI vector will equal
the number of energy counts detected between 7.25 and 7.75 keV for
that spectrum.
In Act 1106, the ROI vector may be normalized using any of a
variety of normalizing functions. For example, the ROI vector may
be L1 or L-Infinity normalized. For example, using L1 normalizing,
each ROI value may divided by the sum of all of the ROI values,
whereas using L-Infinity normalizing, each ROI value may be divided
by a maximum value. Normalizing the ROI vector may reduce the
effects from variances in surface areas of the pieces of material
that are sorted and the surface areas of the reference spectra.
Further, normalizing the ROI vector also reduces the effects of
variances in the irradiation flux of the one or more stimuli,
variances in the fluorescent yield of each piece of material and
reference sample, and variances in the acquisition times for pieces
of material and reference samples.
In Act 1108, for each ROI of the ROI vector, a peak value of the
ROI may be estimated. For example, a shaping function may be
applied to the ROI value for each ROI in the ROI vector. Any of a
variety of shaping functions may be used, for example, a Gaussian
distribution function, a Poisson distribution function or another
suitable function. If a Gaussian distribution function is used,
then the Full Width Have Maximum (FWHM) technique may be used. By
applying a shaping function to each ROI value, the peak value of a
mature spectrum may be predicted (i.e., estimated) from the
immature spectrum built from the detected first and second
emissions. This technique for estimating a peak value for the ROI
enables an accurate classification to be made for a piece of
material even though the emissions were detected for the piece of
material over a very brief period of time, as short as 10
milliseconds or less. Accordingly, pieces of material can be sorted
at a much faster rate than they otherwise could be sorted. Further,
by reducing an entire spectra of emissions data to a vector of
values, namely a vector of estimated peaks, the amount of data that
must be subsequently analyzed to classify the piece of material is
substantially reduced. This reduction of data reduces the amount of
computations that must subsequently be performed, which further
increases the rate at which pieces can be sorted.
Is should be appreciated that the peak values of the ROI for
reference spectra may be determined by stimulating and detecting a
piece of the reference material over a relatively long period of
time, e.g., five seconds. Such a long period of detection produces
a relatively mature XRF and/or optical spectra for the reference
material, from which the peak spectra can be measured or estimated
as described above.
In Act 1110, the piece of material may be classified based on the
estimated peak values using any of a variety of techniques. In one
or more embodiments, the piece of material may be classified based
on the estimated peak values at least similar to as described in
the Sommer patent, step 59 of FIGS. 2A, 2B and 6. However, instead
of calculating the root-mean-square for all energy levels within
the one or more emissions spectra, the root-mean-square method
could be applied only to the estimated peak values. In one or more
alternative embodiments, the "distance method" or the "Tree method"
described in U.S. Pat. No. 5,663,997, titled "Glass Composition
Determination Method and Apparatus," by Willis et al. ("the Willis
patent") may be used to classify the piece of material based on the
estimated peak values. The "distance method" and the "Tree method"
of the Willis patent are described in col. 7, line 8-col. 10, line
11 and in FIGS. 7A-7C, the contents of which are hereby
incorporated by reference.
In one or more embodiments, classifying a piece of material, for
example, based on estimated peaks, may involve the use of neural
networks.
Methods 1000 and 1100 each may include additional acts. Further,
the order of the acts performed as part of method 1000 is not
limited to the order illustrated in FIG. 10 as the acts may be
performed in other orders, and one or more of the acts of method
1000 may be performed in series or in parallel to one or more other
acts, or parts thereof. For example, any of Acts 1002-1008 or parts
thereof, may be performed in parallel for a given piece.
Methods 1000 and 1100 are merely illustrative embodiments of a
methods of sorting and classifying respectively, pieces of
material. Such illustrative embodiments are not intended to limit
the scope of the invention, as any of numerous other
implementations of classifying and sorting pieces of material, for
example, variations of methods 1000 and 1100, are possible and are
intended to fall within the scope of the invention.
Methods 1000 and 1100, acts thereof and various embodiments and
variations of these methods and acts, individually or in
combination, may be defined by computer-readable signals tangibly
embodied on a computer-readable medium, for example, a non-volatile
recording medium, an integrated circuit memory element, or a
combination thereof. Such signals may define instructions, for
example, as part of one or more programs, that, as a result of
being executed by a computer, instruct the computer to perform one
or more of the methods or acts described herein, and/or various
embodiments, variations and combinations thereof. Such instructions
may be written in any of a plurality of programming languages, for
example, Java, Visual Basic, C, C#, or C++, Fortran, Pascal,
Eiffel, Basic, COBOL, etc., or any of a variety of combinations
thereof. The computer-readable medium on which such instructions
are stored may reside on one or more of the components of module
216 described above, and may be distributed across one or more of
such components.
The computer-readable medium may be transportable such that the
instructions stored thereon can be loaded onto any computer system
resource to implement the aspects of the present invention
discussed herein. In addition, it should be appreciated that the
instructions stored on the computer-readable medium, described
above, are not limited to instructions embodied as part of an
application program running on a host computer. Rather, the
instructions may be embodied as any type of computer code (e.g.,
software or microcode) that can be employed to program a processor
to implement the above-discussed aspects of the present
invention.
It should be appreciated that any single component or collection of
multiple components of a computer system, for example, the computer
system described below in relation to FIGS. 12 and 13, that perform
the functions described above in relation to methods 1000 and 1100
can be generically considered as one or more controllers that
control the above-discussed functions. The one or more controllers
can be implemented in numerous ways, such as with dedicated
hardware, or using a processor that is programmed using microcode
or software to perform the functions recited above.
It should be appreciated that any single component or collection of
multiple components of a computer system, for example, the computer
system described below in relation to FIGS. 12 and 13, that perform
the functions described above with respect to describe or reference
the method can be generically considered as one or more controllers
that control the above-discussed functions. The one or more
controllers can be implemented in numerous ways, such as with
dedicated hardware, or using a processor that is programmed using
microcode or software to perform the functions recited above.
Various embodiments according to the invention may be implemented
on one or more computer systems. These computer systems, may be,
for example, general-purpose computers such as those based on Intel
PENTIUM-type processor, Motorola PowerPC, Sun UltraSPARC,
Hewlett-Packard PA-RISC processors, or any other type of processor.
It should be appreciated that one or more of any type computer
system may be used to classify and sort pieces of material based on
emissions resulting from one or more sources of stimuli according
to various embodiments of the invention. Further, the software
design system may be located on a single computer or may be
distributed among a plurality of computers attached by a
communications network.
A general-purpose computer system according to one embodiment of
the invention is configured to classify and sort pieces of material
based on emissions resulting from one or more sources of stimuli.
It should be appreciated that the system may perform other
functions, and the invention is not limited to having any
particular function or set of functions.
For example, various aspects of the invention may be implemented as
specialized software executing in a general-purpose computer system
1200 such as that shown in FIG. 12. The computer system 1200 may
include a processor 1203 connected to one or more memory devices
1204, such as a disk drive, memory, or other device for storing
data. Memory 1204 is typically used for storing programs and data
during operation of the computer system 1200. Components of
computer system 1200 may be coupled by an interconnection mechanism
1205, which may include one or more busses (e.g., between
components that are integrated within a same machine) and/or a
network (e.g., between components that reside on separate discrete
machines). The interconnection mechanism 1205 enables
communications (e.g., data, instructions) to be exchanged between
system components of system 1200. Computer system 1200 also
includes one or more input devices 1202, for example, a keyboard,
mouse, trackball, microphone, touch screen, and one or more output
devices 1201, for example, a printing device, display screen,
speaker. In addition, computer system 1200 may contain one or more
interfaces (not shown) that connect computer system 1200 to a
communication network (in addition or as an alternative to the
interconnection mechanism AO5.
The storage system 1206, shown in greater detail in FIG. 13,
typically includes a computer readable and writeable nonvolatile
recording medium 1301 in which signals are stored that define a
program to be executed by the processor or information stored on or
in the medium 1301 to be processed by the program. The medium may,
for example, be a disk or flash memory. Typically, in operation,
the processor causes data to be read from the nonvolatile recording
medium 1301 into another memory 1302 that allows for faster access
to the information by the processor than does the medium 1301. This
memory 1302 is typically a volatile, random access memory such as a
dynamic random access memory (DRAM) or static memory (SRAM). It may
be located in storage system 1206, as shown, or in memory system
1204, not shown. The processor 1203 generally manipulates the data
within the integrated circuit memory 1204, 1302 and then copies the
data to the medium 1301 after processing is completed. A variety of
mechanisms are known for managing data movement between the medium
1301 and the integrated circuit memory element 1204, 1302, and the
invention is not limited thereto. The invention is not limited to a
particular memory system 1204 or storage system 1206.
The computer system may include specially-programmed,
special-purpose hardware, for example, an application-specific
integrated circuit (ASIC). Aspects of the invention may be
implemented in software, hardware or firmware, or any suitable
combination thereof. Further, such methods, acts, systems, system
elements and components thereof may be implemented as part of the
computer system described above or as an independent component.
Although computer system 1200 is shown by way of example as one
type of computer system upon which various aspects of the invention
may be practiced, it should be appreciated that aspects of the
invention are not limited to being implemented on the computer
system as shown in FIG. 12. Various aspects of the invention may be
practiced on one or more computers having a different architecture
or components that that shown in FIG. 12.
Computer system 1200 may be a general-purpose computer system that
is programmable using a high-level computer programming language.
Computer system 1200 may be also implemented using specially
programmed, special purpose hardware. In computer system 1200,
processor 1203 is typically a commercially available processor such
as the well-known Pentium class processor available from the Intel
Corporation. Many other processors are available. Such a processor
usually executes an operating system which may be, for example, the
Windows 95, Windows 98, Windows NT, Windows 2000 (Windows ME) or
Windows XP operating systems available from the Microsoft
Corporation, MAC OS System X available from Apple Computer, the
Solaris Operating System available from Sun Microsystems, or UNIX
available from various sources. Many other operating systems may be
used.
The processor and operating system together define a computer
platform for which application programs in high-level programming
languages are written. It should be understood that the invention
is not limited to a particular computer system platform, processor,
operating system, or network. Also, it should be apparent to those
skilled in the art that the present invention is not limited to a
specific programming language or computer system. Further, it
should be appreciated that other appropriate programming languages
and other appropriate computer systems could also be used.
One or more portions of the computer system may be distributed
across one or more computer systems (not shown) coupled to a
communications network. These computer systems also may be
general-purpose computer systems. For example, various aspects of
the invention may be distributed among one or more computer systems
configured to provide a service (e.g., servers) to one or more
client computers, or to perform an overall task as part of a
distributed system. For example, various aspects of the invention
may be performed on a client-server system that includes components
distributed among one or more server systems that perform various
functions according to various embodiments of the invention. These
components may be executable, intermediate (e.g., IL) or
interpreted (e.g., Java) code which communicate over a
communication network (e.g., the Internet) using a communication
protocol (e.g., TCP/IP).
It should be appreciated that the invention is not limited to
executing on any particular system or group of systems. Also, it
should be appreciated that the invention is not limited to any
particular distributed architecture, network, or communication
protocol.
Various embodiments of the present invention may be programmed
using an object-oriented programming language, such as SmallTalk,
Java, C++, Ada, or C# (C-Sharp). Other object-oriented programming
languages may also be used. Alternatively, functional, scripting,
and/or logical programming languages may be used. Various aspects
of the invention may be implemented in a non-programmed environment
(e.g., documents created in HTML, XML or other format that, when
viewed in a window of a browser program, render aspects of a
graphical-user interface (GUI) or perform other functions). Various
aspects of the invention may be implemented as programmed or
non-programmed elements, or any suitable combination thereof.
As previously mentioned in this application, the classification
module 930 may be configured to classify materials using any of a
plurality of types of techniques, for example, as described in the
Sommer patent in relation to step 59 in FIGS. 2a, 2b, and 6 of that
patent. Included herein are FIGS. 2a, 2b, and 6 of that patent
(renumbered as FIGS. 14A, 14B, and 15), which are now
described.
FIGS. 14A and 14B is a flow chart depicting an exemplary
illustrative embodiment of a process of sorting materials at high
speeds. First, in step 1451, materials are fed in a singulated
stream onto a conveyor belt. In an optional aspect of this
illustrative embodiment, the materials are flattened with a
flattening apparatus before being fed onto a conveyor belt. For
example, a rolls crusher may be used for this purpose.
By flattening the piece of material, any other materials adhered to
the piece of material may be removed. Further, flattening a piece
of material before feeding the piece onto the conveyor belt
improves sorting and classification of the materials. First,
flattened pieces of material remain stationary on the conveyor
belt, and do not roll. Thus, in the illustrative embodiment of FIG.
1 (of the Sommer patent), when a piece of material is classified,
and an appropriate airjet is actuated, the piece is in a position
anticipated by an xrf processing module, and the piece is ejected
from the conveyor belt into an appropriate sorting bin. Second,
flattening the pieces of material provides a larger surface area to
irradiate and from which to detect x-rays. Consequently, the piece
of material is bombarded with and fluoresces more x-rays, resulting
in a more complete xrf spectrum being determined for the piece of
material. Third, the composition of the piece of material is less
influenced by surface contaminants. Because during flattening,
fresh material surfaces are exposed, a cleaner xrf spectrum is to
produced. Consequently, the spectra detected are more
representative of the piece of material and not other materials
that may be adhering to the surface of the piece of material.
In an illustrative embodiment, the conveyor belt (of the Sommer
patent) is depressed or troughed in the center such that pieces of
materials gravitate to the center of the conveyor belt, where they
remain more stationary and may be aligned directly beneath a
detector.
Next, in step 1453, the materials are conveyed along the conveyor
belt and into an x-ray detection chamber. In an illustrative
embodiment, each piece is flattened while being conveyed along the
belt, as discussed above in connection with step 1451.
In an illustrative embodiment, the belt is comprised at least
mostly of a material such as, for example, polyvinyl chloride
(PVC), that when irradiated, fluoresce x-rays only at low energy
levels. The speed at which the belt is operated is programmed in
accordance with the spacing between the pieces of material and the
cumulative time which it takes to: acquire or detect the x-rays
from a piece of material; determine an xrf spectrum; and classify
the piece. Such speeds may exceed 100 inches per second.
In step 1455, when a piece of material has entered the x-ray
detection chamber, the piece is irradiated with x-rays. The
exposure to x-rays causes each material to fluoresce x-rays at
various energy levels, producing an xrf spectrum. In step 1457,
this xrf spectrum is detected by an x-ray detector.
Next, in step 1459, for each piece of material, the material is
classified based on the xrf that was detected.
Next, in step 1461 of FIG. 14B, an air jet corresponding to the
classification of the piece is activated. Between the time at which
the piece of material was irradiated and the time at which the air
jet is activated, the piece of material has moved from the
detection chamber to a point downstream from the detection chamber,
at the rate of conveying of the belt. In an embodiment, the
activation of the air jet is timed such that as the piece passes
the air jet mapped to the classification of the piece, the air jet
is activated and the piece of material is ejected from the conveyor
belt.
In an alternative embodiment, the activation of air jet is timed by
a respective position detector that detects when a piece of
material is passing before the air jet and sends a signal to enable
the activation of the jet. In step 1463, the sorting bin
corresponding to the airjet that was activated receives the ejected
piece of material.
The sorting application, also referred to herein as the
classification module, executes a sorting algorithm that classifies
the piece of material by recognizing the spectral pattern of the to
xrf spectrum of the piece. FIG. 15 is a flow chart showing an
illustrative embodiment of step 1459 of FIG. 14A for classifying
the piece based on the xrf spectrum of the material. In step 1561,
each energy count of the xrf spectrum is normalized such that each
energy count may be considered a dimensional component of an xrf
unit vector. Accordingly, each energy count is reduced by an amount
equal to:
.times..times..times. ##EQU00001## where a, b, c and n are energy
counts at various energy levels.
The energy range of the xrf spectrum determined by a spectrum
acquisition module, the number of energy levels of the determined
xrf spectrum, and the resolution of the determined xrf spectrum are
all programmable. These parameters may be chosen depending on the
sort to be performed. If a large range of materials are being
sorted, the energy range may be large and the number of energy
levels high. If pieces of materials are to be sorted have
relatively similar compositions, then the resolution may be fine,
so as to distinguish between the spectral patterns. For example,
when pieces of metal are to be sorted into aluminum, brass, chrome
plated zinc, copper, stainless steel, and zinc, the spectrum
acquisition module may be programmed to detect and count x-rays at
256 energy levels ranging from 0 key to 25.6 key with 0.1 key
resolution.
Next, in step 1563, the vector dot products are computed between
the normalized detected xrf spectrum and the normalized xrf spectra
of any stored reference materials. Prior to starting the sorting
process, a set of reference samples is collected and the xrf
spectra of these samples determined and stored, for example, in a
non-volatile storage medium. In an illustrative embodiment, for
reference spectra, the x-ray spectrum of each reference material is
collected over an interval of 5 seconds.
To compute the dot product, if the detected normalized reference
spectra has normalized energy counts of a.sub.1, a.sub.2, . . .
a.sub.256, and the normalized xrf spectrum of a reference material
has normalized energy counts of b.sub.1, b.sub.2, . . . b.sub.256,
then the vector dot product between these two spectra would be
a.sub.1.times.b.sub.1+a.sub.2.times.b.sub.2+ . . .
a.sub.256.times.b.sub.256. Because all the spectra have been
normalized to a unit vector, the dot products between two identical
spectra would produce the value 1, where the results of all dot
products should be between the 1 and 0. A dot product of 0 results
if for every energy level of the detected spectrum for which at
least a single count is to detected, the reference spectrum does
not have a single energy count, or vice versa.
A user interface provides functions to sample, view, and compare
individual spectrums to prepare the reference material set and to
designate which references will be "active" and read into faster
volatile memory for use during execution of the sorting algorithm.
Thus, the xrf processing module computes a vector dot product
between the normalized xrf of the detected material and the
normalized xrf spectrum of each of the active reference
materials.
Next, in step 1565, it is determined whether any of the computed
vector dot products reach a minimum threshold value. In an
illustrative embodiment, there is a single minimum threshold value
that must be achieved for any of the reference spectra. In an
alternative illustrative embodiment, each reference spectrum has an
individual minimum threshold value that the dot product calculated
for the reference spectrum must equal or exceed. Having an
individual threshold value for each reference spectrum adds
additional flexibility in distinguishing between similar spectral
patterns, as is discussed in more detail below.
The threshold values for reference spectra are programmable by a
system user. The closer the spectral patterns of two reference
spectra, the higher the threshold value for these reference spectra
should be programmed in order to positively distinguish the two
spectra. For example, if a user is only interested in
distinguishing between a first spectral pattern that has several
peaks at certain energy levels, and a second spectral pattern that
has energy peaks at certain other energy levels, then the user may
program the threshold value for these two reference spectra to be
relatively low to distinguish between the two spectral patterns
(although the threshold value should be high enough to distinguish
the two reference spectra from other reference spectra).
Conversely, if two spectral patterns have energy peaks that share
common energy levels and where, for these energy levels, the
normalized count value for each spectra is close to the other, then
the threshold value should be set relatively high. The value of the
threshold must be set high enough so that the spectral pattern of a
detected piece of material must be very close to matching one of
the two reference spectra for a classification to be made. This
high threshold ensures correct recognition of a spectral
pattern.
If it is determined in step 1565 that at least one vector dot
product reaches a minimum threshold value, then at step 1567 it is
determined which computer dot product value has the highest value.
The dot product of the highest value indicates the reference
spectra closest to the detected spectra. In an alternative
illustrative embodiment, where each spectrum has an individual
threshold value, it is determined for which of the reference
spectra the highest dot product was calculated for which the
minimum threshold for the reference material was to reached.
Consequently, in step 1569, the classification corresponding to the
stored spectrum that produced the highest dot product and equals or
exceeds a minimum threshold is determined. Such a classification
may be encoded on a classification signal. In an alternative
illustrative embodiment of step 1569, the classification
corresponding to the stored spectrum whose dot product exceeds the
spectrum's threshold value by the greatest percentage is selected.
For example, assume spectra A has a threshold of 0.4 and spectra B
has a threshold of 0.6. In addition, assume a dot product of 0.7 is
calculated for spectra A and a dot product of 0.8 is calculated for
spectra B. The classification corresponding to Spectra A would be
selected even though Spectra B's dot product is higher because
Spectra A's dot product is 75% over its threshold, while Spectra
B's dot product is only 33% over its threshold.
Classifying a piece of material by comparing the spectral shape or
spectral pattern of the xrf of a spectrum contrasts to known
methods of analyzing only energy counts of select peak energy
levels. Such known methods merely determine whether the number of
counts for select energy level exceeds a threshold value, or
compare the counts of the select energy levels to the counts from
corresponding select peak energy levels of a reference spectrum.
Each selected energy level is typically indicative of a particular
element present in the piece of material. In some known systems,
the selected peaks are normalized, such that the resulting
normalized peaks reflect the proportion of each element in the
piece of material. Typically, known methods require that the xrf of
a piece of material is detected over a relatively long period of
time such as, for example, a second or more. Detecting over such a
long period ensures that the selected peaks accurately reflect the
proportion of each element.
The sorting algorithm described herein is a faster and more
flexible method of classifying a piece of material than those known
methods described above. First, comparing the spectral pattern or
image of the detected xrf spectrum to the spectral pattern or image
of stored reference spectra permits an accurate classification to
be made even when only a faint or weak image of the xrf spectrum of
a piece of material is known (i.e. the detected spectral pattern
takes the general shape of the spectral pattern of a reference
spectrum). Therefore, precise composition of a piece of material
need not actually be determined (although it may be). Such a faint
image results when a relatively limited number of x-rays or counts
have been detected. Less counts result from shorter detection
times. Thus, recognition of a faint image permits a piece of
material to be classified in shorter detection times, substantially
less than one second, possibly shorter than 10 ms.
Second, the sorting algorithm described herein permits a material
sorting system to have greater flexibility in sorting materials
than do known sorting algorithms allow. A user may select a random
sample to use as a reference sample, establish the random sample as
a reference spectra by detecting the xrf from the random sample for
a relatively long interval of time, for example 5 seconds, in order
to eliminate any random variations in the detected xrf, and store
the xrf spectrum determined from the detected x-rays. The xrf
spectrum of the random sample can then serve as a reference spectra
by which other pieces of material can be detected and compared
against to determine whether the determined xrf spectra matches the
reference spectra created from the random sample. A user would not
have to program the processing module to analyze certain peak
energy levels of the new reference xrf spectrum and future
determined xrf spectra. In contrast, the sorting algorithm would
compare the spectral patterns without regard for peak energy
levels. Known sorting methods require that sorting parameters be
reconfigured to analyze the peak energy levels of the reference xrf
spectra and determined xrf spectra.
Having now described some illustrative embodiments of the
invention, it should be apparent to those skilled in the art that
the foregoing is merely illustrative and not limiting, having been
presented by way of example only. Numerous modifications and other
illustrative embodiments are within the scope of one of ordinary
skill in the art and are contemplated as falling within the scope
of the invention. In particular, although many of the examples
presented herein involve specific combinations of method acts or
system elements, it should be understood that those acts and those
elements may be combined in other ways to accomplish the same
objectives. Acts, elements and features discussed only in
connection with one embodiment are not intended to be excluded from
a similar role in other embodiments. Further, for the one or more
means-plus-function limitations recited in the following claims,
the means are not intended to be limited to the means disclosed
herein for performing the recited function, but are intended to
cover in scope any equivalent means, known now or later developed,
for performing the recited function.
As used herein, whether in the written description or the claims,
the terms "comprising", "including", "carrying", "having",
"containing", "involving", and the like are to be understood to be
open-ended, i.e., to mean including but not limited to. Only the
transitional phrases "consisting of" and "consisting essentially
of" respectively, shall be closed or semi-closed transitional
phrases, as set forth, with respect to claims, in the United States
Patent Office Manual of Patent Examining Procedures (Original
Eighth Edition, August 2001), to Section 2111.03.
Use of ordinal terms such as "first", "second", "third", etc., in
the claims to modify a claim element does not by itself connote any
priority, precedence, or order of one claim element over another or
the temporal order in which acts of a method are performed, but are
used merely as labels to distinguish one claim element having a
certain name from another element having a same name (but for use
of the ordinal term) to distinguish the claim elements.
* * * * *
References